BibSLEIGH
BibSLEIGH corpus
BibSLEIGH tags
BibSLEIGH bundles
BibSLEIGH people
EDIT!
CC-BY
Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
email twitter
graph
Google graph

Tag #graph

2876 papers:

PADLPADL-2020-ChanC #distance #edit distance #flexibility #programming #set #using
Flexible Graph Matching and Graph Edit Distance Using Answer Set Programming (SCC, JC), pp. 20–36.
PADLPADL-2020-TarauB #interactive #mining #prolog
Interactive Text Graph Mining with a Prolog-based Dialog Engine (PT, EB0), pp. 3–19.
ASPLOSASPLOS-2020-KalinskyKE #architecture #relational
The TrieJax Architecture: Accelerating Graph Operations Through Relational Joins (OK, BK, YE), pp. 1217–1231.
CCCC-2020-BrauckmannGEC #learning #modelling
Compiler-based graph representations for deep learning models of code (AB, AG, SE, JC), pp. 201–211.
CGOCGO-2020-ChenPPLR #adaptation #named
ATMem: adaptive data placement in graph applications on heterogeneous memories (YC, IBP, ZP, XL, BR), pp. 293–304.
CGOCGO-2020-ZhangBCDKAS #algorithm #optimisation #order
Optimizing ordered graph algorithms with GraphIt (YZ, AB, XC, LD, SK, SPA, JS), pp. 158–170.
EDMEDM-2019-DavisWY #education #n-gram #topic
N-gram Graphs for Topic Extraction in Educational Forums (GMD, CW, CY).
EDMEDM-2019-HuR #estimation #network #performance
Academic Performance Estimation with Attention-based Graph Convolutional Networks (QH, HR).
EDMEDM-2019-Venantd #complexity #concept #predict #semantics #towards
Towards the Prediction of Semantic Complexity Based on Concept Graphs (RV, Md).
ICSMEICSME-2019-SunXCBW0 #programming
Know-How in Programming Tasks: From Textual Tutorials to Task-Oriented Knowledge Graph (JS, ZX, RC, HB, JW, XP0), pp. 257–268.
MSRMSR-2019-BenelallamHSBB #dependence #representation
The maven dependency graph: a temporal graph-based representation of maven central (AB, NH, CSV, BB, OB), pp. 344–348.
MSRMSR-2019-PietriSZ #dataset #development
The software heritage graph dataset: public software development under one roof (AP, DS, SZ), pp. 138–142.
SANERSANER-2019-XieCYLHDZ #approach #learning #named
DeepLink: A Code Knowledge Graph Based Deep Learning Approach for Issue-Commit Link Recovery (RX, LC, WY0, ZL, TH, DD, SZ), pp. 434–444.
CIAACIAA-2019-FujiyoshiP #automaton #finite #set
A Simple Extension to Finite Tree Automata for Defining Sets of Labeled, Connected Graphs (AF, DP), pp. 121–132.
AIIDEAIIDE-2019-WareGSF #experience #multi
Multi-Agent Narrative Experience Management as Story Graph Pruning (SGW, ETG, AS, RF), pp. 87–93.
CoGCoG-2019-AbuzuraiqFP #clustering #framework #generative #named
Taksim: A Constrained Graph Partitioning Framework for Procedural Content Generation (AMA, AF, PP), pp. 1–8.
CoGCoG-2019-BarzdinsGBLBC #challenge #database
RDF* Graph Database as Interlingua for the TextWorld Challenge (GB, DG, PFB, UL, GB, EC), pp. 1–2.
CoGCoG-2019-BeigKCM #game studies #named
G-SpAR: GPU-Based Voxel Graph Pathfinding for Spatial Audio Rendering in Games and VR (MB, BK, KC, PMB), pp. 1–8.
CoGCoG-2019-CookR #analysis #automation #game studies
Hyperstate Space Graphs for Automated Game Analysis (MC0, AR), pp. 1–8.
CoGCoG-2019-KimLLHK #algorithm #automation #game studies #generative #using
Automatic Generation of Game Content using a Graph-based Wave Function Collapse Algorithm (HK, SL, HL, TH, SK), pp. 1–4.
CoGCoG-2019-LipinskiSRA #generative #incremental #using
Level Graph - Incremental Procedural Generation of Indoor Levels using Minimum Spanning Trees (BvRL, SS, JR, DA), pp. 1–7.
CoGCoG-2019-Wallne
Enhancing Battle Maps through Flow Graphs (GW), pp. 1–4.
FDGFDG-2019-PartlanCKSHSMSE #evaluation #interactive #representation
Evaluation of an automatically-constructed graph-based representation for interactive narrative (NP, EC, EK, SS, CH, GS, CM, SCS, MSEN), p. 9.
CIKMCIKM-2019-0002CZTZG #classification #named
Meta-GNN: On Few-shot Node Classification in Graph Meta-learning (FZ0, CC, KZ, GT, TZ, JG), pp. 2357–2360.
CIKMCIKM-2019-AdriaensABGL
Discovering Interesting Cycles in Directed Graphs (FA, ÇA, TDB, AG, JL), pp. 1191–1200.
CIKMCIKM-2019-BaiYK0LY #network #predict
Spatio-Temporal Graph Convolutional and Recurrent Networks for Citywide Passenger Demand Prediction (LB, LY, SSK, XW0, WL0, ZY), pp. 2293–2296.
CIKMCIKM-2019-BespinyowongT #named
kBrowse: kNN Graph Browser (RB, AKHT), pp. 2933–2936.
CIKMCIKM-2019-ChekolS #performance
Leveraging Graph Neighborhoods for Efficient Inference (MWC, HS), pp. 1893–1902.
CIKMCIKM-2019-ChenLYZS #network
Knowledge-aware Textual Entailment with Graph Attention Network (DC, YL, MY0, HTZ, YS), pp. 2145–2148.
CIKMCIKM-2019-ChristmannRASW #using
Look before you Hop: Conversational Question Answering over Knowledge Graphs Using Judicious Context Expansion (PC, RSR, AA, JS, GW), pp. 729–738.
CIKMCIKM-2019-DongZHSL #detection #multi #network
Multiple Rumor Source Detection with Graph Convolutional Networks (MD, BZ, NQVH, HS, GL), pp. 569–578.
CIKMCIKM-2019-DuanX #enterprise #information management
Enterprise Knowledge Graph From Specific Business Task to Enterprise Knowledge Management (RD, YX), pp. 2965–2966.
CIKMCIKM-2019-DuttaL #clique #statistics
Finding a Maximum Clique in Dense Graphs via χ2 Statistics (SD0, JL), pp. 2421–2424.
CIKMCIKM-2019-FanZDCSL #approach #identification #learning #network #novel
Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network Approach (CF, LZ, YD, MC, YS, ZL), pp. 559–568.
CIKMCIKM-2019-HouFZYLWWXS #android #detection #named #robust
αCyber: Enhancing Robustness of Android Malware Detection System against Adversarial Attacks on Heterogeneous Graph based Model (SH, YF, YZ, YY, JL, WW, JW, QX, FS), pp. 609–618.
CIKMCIKM-2019-HuangYX #detection #learning
System Deterioration Detection and Root Cause Learning on Time Series Graphs (HH, SY, YX), pp. 2537–2545.
CIKMCIKM-2019-IslamMR #named #network #predict #social #using
NActSeer: Predicting User Actions in Social Network using Graph Augmented Neural Network (MRI, SM, NR), pp. 1793–1802.
CIKMCIKM-2019-JiangWZSLL #detection #learning #representation
Cross-domain Aspect Category Transfer and Detection via Traceable Heterogeneous Graph Representation Learning (ZJ, JW, LZ, CS, YL, XL), pp. 289–298.
CIKMCIKM-2019-JiaoXZZ #network #predict
Collective Link Prediction Oriented Network Embedding with Hierarchical Graph Attention (YJ, YX, JZ, YZ), pp. 419–428.
CIKMCIKM-2019-JinOLLLC #learning #semantics #similarity
Learning Region Similarity over Spatial Knowledge Graphs with Hierarchical Types and Semantic Relations (XJ, BO, SL, DL, KHL, LC), pp. 669–678.
CIKMCIKM-2019-LeeRKKKR #network
Graph Convolutional Networks with Motif-based Attention (JBL, RAR, XK, SK, EK, AR), pp. 499–508.
CIKMCIKM-2019-LiCWZW #feature model #interactive #modelling #named #network #predict
Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction (ZL, ZC, SW, XZ, LW0), pp. 539–548.
CIKMCIKM-2019-LiGLCYN #hashtag #network #recommendation
Long-tail Hashtag Recommendation for Micro-videos with Graph Convolutional Network (ML, TG, ML, ZC, JY, LN), pp. 509–518.
CIKMCIKM-2019-LiQLYL #detection #network #overview
Spam Review Detection with Graph Convolutional Networks (AL, ZQ, RL, YY, DL), pp. 2703–2711.
CIKMCIKM-2019-LiuWYZSMZGZYQ #learning #mobile #optimisation #representation
Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing (ZL, DW, QY, ZZ, YS, JM, WZ, JG, JZ, SY, YQ), pp. 2577–2584.
CIKMCIKM-2019-LiuZH #network #representation #towards
Towards Explainable Representation of Time-Evolving Graphs via Spatial-Temporal Graph Attention Networks (ZL, DZ, JH), pp. 2137–2140.
CIKMCIKM-2019-LiYH #clustering #realtime
Real-time Edge Repartitioning for Dynamic Graph (HL, HY, JH), pp. 2125–2128.
CIKMCIKM-2019-MaAWSCTY #data analysis #learning #similarity
Deep Graph Similarity Learning for Brain Data Analysis (GM, NKA, TLW, DS, MWC, NBTB, PSY), pp. 2743–2751.
CIKMCIKM-2019-MauryaLM #approximate #network #performance
Fast Approximations of Betweenness Centrality with Graph Neural Networks (SKM, XL0, TM), pp. 2149–2152.
CIKMCIKM-2019-MohantyR #effectiveness #named #towards
Insta-Search: Towards Effective Exploration of Knowledge Graphs (MM, MR), pp. 2909–2912.
CIKMCIKM-2019-QiuLHY #network #order #recommendation
Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks (RQ, JL, ZH, HY), pp. 579–588.
CIKMCIKM-2019-SalhaLHTV #predict
Gravity-Inspired Graph Autoencoders for Directed Link Prediction (GS, SL, RH, VAT, MV), pp. 589–598.
CIKMCIKM-2019-Sanei-MehriZST #estimation #named
FLEET: Butterfly Estimation from a Bipartite Graph Stream (SVSM, YZ, AES, ST), pp. 1201–1210.
CIKMCIKM-2019-ShenTB #learning #representation
GRLA 2019: The first International Workshop on Graph Representation Learning and its Applications (HS, JT, PB), pp. 2997–2998.
CIKMCIKM-2019-ShresthaMAV #behaviour #interactive #learning #social
Learning from Dynamic User Interaction Graphs to Forecast Diverse Social Behavior (PS, SM, DA, SV), pp. 2033–2042.
CIKMCIKM-2019-VakulenkoGPRC #message passing
Message Passing for Complex Question Answering over Knowledge Graphs (SV, JDFG, AP, MdR, MC), pp. 1431–1440.
CIKMCIKM-2019-VazirgiannisNS #kernel #machine learning
Machine Learning on Graphs with Kernels (MV, GN, GS), pp. 2983–2984.
CIKMCIKM-2019-Wang0C #learning #reasoning #recommendation
Learning and Reasoning on Graph for Recommendation (XW, XH0, TSC), pp. 2971–2972.
CIKMCIKM-2019-WangRCR0R #learning #predict
Order-free Medicine Combination Prediction with Graph Convolutional Reinforcement Learning (SW, PR, ZC, ZR, JM0, MdR), pp. 1623–1632.
CIKMCIKM-2019-WuPDTZD #distance #learning #network
Long-short Distance Aggregation Networks for Positive Unlabeled Graph Learning (MW, SP, LD, IWT, XZ, BD), pp. 2157–2160.
CIKMCIKM-2019-XieXYZ #multi
EHR Coding with Multi-scale Feature Attention and Structured Knowledge Graph Propagation (XX, YX, PSY, YZ), pp. 649–658.
CIKMCIKM-2019-XuHY #learning #network #scalability
Scalable Causal Graph Learning through a Deep Neural Network (CX, HH, SY), pp. 1853–1862.
CIKMCIKM-2019-XuLHLX0 #e-commerce #network #recommendation #social
Relation-Aware Graph Convolutional Networks for Agent-Initiated Social E-Commerce Recommendation (FX, JL, ZH, YL0, YX, XX0), pp. 529–538.
CIKMCIKM-2019-YangWCW #network #predict #using
Using External Knowledge for Financial Event Prediction Based on Graph Neural Networks (YY, ZW, QC, LW), pp. 2161–2164.
CIKMCIKM-2019-YeWYJZXY #behaviour #network #representation
Bayes EMbedding (BEM): Refining Representation by Integrating Knowledge Graphs and Behavior-specific Networks (YY, XW, JY, KJ, JZ, YX, HY), pp. 679–688.
CIKMCIKM-2019-ZhangG0G #evolution #on the
On Continuously Matching of Evolving Graph Patterns (QZ, DG, XZ0, AG), pp. 2237–2240.
CIKMCIKM-2019-ZhaoCXLZ0 #classification
Hashing Graph Convolution for Node Classification (WZ, ZC, CX, CL, TZ0, JY0), pp. 519–528.
CIKMCIKM-2019-ZhaoPZZWZXJ #distributed #scalability #visual notation
Large-Scale Visual Search with Binary Distributed Graph at Alibaba (KZ, PP, YZ, YZ, CW, YZ, YX, RJ), pp. 2567–2575.
CIKMCIKM-2019-ZhaoSSW #learning #named #precise #retrieval
GRAPHENE: A Precise Biomedical Literature Retrieval Engine with Graph Augmented Deep Learning and External Knowledge Empowerment (SZ, CS, AS, FW), pp. 149–158.
ECIRECIR-p1-2019-AgarwalRS
Retrieving Relationships from a Knowledge Graph for Question Answering (PA, MR, GMS), pp. 35–50.
ECIRECIR-p1-2019-DavilaJSGZ #image #named #using
Tangent-V: Math Formula Image Search Using Line-of-Sight Graphs (KD, RJ, SS, VG, RZ), pp. 681–695.
ECIRECIR-p1-2019-FlorescuJ #learning #representation
A Supervised Keyphrase Extraction System Based on Graph Representation Learning (CF, WJ), pp. 197–212.
ECIRECIR-p1-2019-KishimotoHASK
Binarized Knowledge Graph Embeddings (KK, KH, GA, MS, KK), pp. 181–196.
ECIRECIR-p1-2019-MackenzieMPCS #recursion
Compressing Inverted Indexes with Recursive Graph Bisection: A Reproducibility Study (JM, AM, MP, JSC, TS), pp. 339–352.
ECIRECIR-p2-2019-HalkidiK #assessment #clustering #named #quality
QGraph: A Quality Assessment Index for Graph Clustering (MH, IK), pp. 70–77.
ICMLICML-2019-0008TO
Hyperbolic Disk Embeddings for Directed Acyclic Graphs (RS0, RT, SO), pp. 6066–6075.
ICMLICML-2019-Abu-El-HaijaPKA #architecture #higher-order #named
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing (SAEH, BP, AK, NA, KL, HH, GVS, AG), pp. 21–29.
ICMLICML-2019-AletJVRLK #adaptation #memory management #network
Graph Element Networks: adaptive, structured computation and memory (FA, AKJ, MBV, AR, TLP, LPK), pp. 212–222.
ICMLICML-2019-BaranchukPSB #learning #similarity
Learning to Route in Similarity Graphs (DB, DP, AS, AB), pp. 475–484.
ICMLICML-2019-BojchevskiG
Adversarial Attacks on Node Embeddings via Graph Poisoning (AB, SG), pp. 695–704.
ICMLICML-2019-BoseH #composition #constraints
Compositional Fairness Constraints for Graph Embeddings (AJB, WLH), pp. 715–724.
ICMLICML-2019-ChenW0R #algorithm #incremental #performance
Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications (PYC, LW, SL0, IR), pp. 1091–1101.
ICMLICML-2019-CortesDGMY #feedback #learning #online
Online Learning with Sleeping Experts and Feedback Graphs (CC, GD, CG, MM, SY), pp. 1370–1378.
ICMLICML-2019-CortesDMZG #learning
Active Learning with Disagreement Graphs (CC, GD, MM, NZ, CG), pp. 1379–1387.
ICMLICML-2019-FranceschiNPH #learning #network
Learning Discrete Structures for Graph Neural Networks (LF, MN, MP, XH), pp. 1972–1982.
ICMLICML-2019-GaoJ
Graph U-Nets (HG, SJ), pp. 2083–2092.
ICMLICML-2019-GaoWH #data analysis #geometry
Geometric Scattering for Graph Data Analysis (FG, GW, MJH), pp. 2122–2131.
ICMLICML-2019-GroverZE #generative #modelling #named
Graphite: Iterative Generative Modeling of Graphs (AG, AZ, SE), pp. 2434–2444.
ICMLICML-2019-GuoSH #dependence #learning #relational
Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs (LG, ZS, WH0), pp. 2505–2514.
ICMLICML-2019-HendrickxOS #learning
Graph Resistance and Learning from Pairwise Comparisons (JMH, AO, VS), pp. 2702–2711.
ICMLICML-2019-JeongKKN #modelling #music #network #performance
Graph Neural Network for Music Score Data and Modeling Expressive Piano Performance (DJ, TK, YK, JN), pp. 3060–3070.
ICMLICML-2019-LeeLK #self
Self-Attention Graph Pooling (JL, IL, JK), pp. 3734–3743.
ICMLICML-2019-LiGDVK #learning #network #similarity
Graph Matching Networks for Learning the Similarity of Graph Structured Objects (YL, CG, TD, OV, PK), pp. 3835–3845.
ICMLICML-2019-Ma0KW0 #network
Disentangled Graph Convolutional Networks (JM, PC0, KK, XW0, WZ0), pp. 4212–4221.
ICMLICML-2019-MaoFRAFW #estimation #order #probability
A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs (JM, JNF, TR, MAS, GF, SW), pp. 4343–4351.
ICMLICML-2019-MehtaCR #network #probability
Stochastic Blockmodels meet Graph Neural Networks (NM, LC, PR), pp. 4466–4474.
ICMLICML-2019-MercadoT0 #clustering #matrix
Spectral Clustering of Signed Graphs via Matrix Power Means (PM0, FT, MH0), pp. 4526–4536.
ICMLICML-2019-Murphy0R0 #relational
Relational Pooling for Graph Representations (RLM, BS0, VAR, BR0), pp. 4663–4673.
ICMLICML-2019-ObermeyerBJPCRG
Tensor Variable Elimination for Plated Factor Graphs (FO, EB, MJ, NP, JC, AMR, NDG), pp. 4871–4880.
ICMLICML-2019-QuBT #markov #named #network
GMNN: Graph Markov Neural Networks (MQ, YB, JT0), pp. 5241–5250.
ICMLICML-2019-RieckBB #classification #persistent
A Persistent Weisfeiler-Lehman Procedure for Graph Classification (BR, CB, KMB), pp. 5448–5458.
ICMLICML-2019-SafaviB #multi
Tractable n-Metrics for Multiple Graphs (SS, JB), pp. 5568–5578.
ICMLICML-2019-TzengW #detection #distributed
Distributed, Egocentric Representations of Graphs for Detecting Critical Structures (RCT, SHW), pp. 6354–6362.
ICMLICML-2019-VayerCTCF
Optimal Transport for structured data with application on graphs (TV, NC, RT, LC, RF), pp. 6275–6284.
ICMLICML-2019-WalkerG #process
Graph Convolutional Gaussian Processes (IW, BG), pp. 6495–6504.
ICMLICML-2019-WuSZFYW #network
Simplifying Graph Convolutional Networks (FW, AHSJ, TZ, CF, TY, KQW), pp. 6861–6871.
ICMLICML-2019-XuLZC #learning
Gromov-Wasserstein Learning for Graph Matching and Node Embedding (HX, DL, HZ, LC), pp. 6932–6941.
ICMLICML-2019-YouYL #network
Position-aware Graph Neural Networks (JY, RY, JL), pp. 7134–7143.
ICMLICML-2019-YuCGY #learning #named #network
DAG-GNN: DAG Structure Learning with Graph Neural Networks (YY, JC, TG, MY), pp. 7154–7163.
ICMLICML-2019-ZhangHK #design #distributed #named #network
Circuit-GNN: Graph Neural Networks for Distributed Circuit Design (GZ, HH, DK), pp. 7364–7373.
ICMLICML-2019-ZhuSLHB #fault tolerance #learning
Improved Dynamic Graph Learning through Fault-Tolerant Sparsification (CJZ, SS, KyL, SH, JB), pp. 7624–7633.
KDDKDD-2019-0001WAT #network
Graph Convolutional Networks with EigenPooling (YM0, SW, CCA, JT), pp. 723–731.
KDDKDD-2019-0009ZGZNQH #framework #named #recommendation #scalability
IntentGC: A Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation (JZ0, ZZ, ZG, WZ0, WN, GQ, XH), pp. 2347–2357.
KDDKDD-2019-Chang #clique #performance #scalability
Efficient Maximum Clique Computation over Large Sparse Graphs (LC), pp. 529–538.
KDDKDD-2019-ChiangLSLBH #algorithm #clustering #named #network #performance #scalability
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks (WLC, XL, SS, YL0, SB, CJH), pp. 257–266.
KDDKDD-2019-DengRN #learning #predict #social
Learning Dynamic Context Graphs for Predicting Social Events (SD, HR, YN), pp. 1007–1016.
KDDKDD-2019-FanZHSHML #network #recommendation
Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation (SF, JZ, XH, CS, LH, BM, YL), pp. 2478–2486.
KDDKDD-2019-GaoJ #learning #network #representation
Graph Representation Learning via Hard and Channel-Wise Attention Networks (HG, SJ), pp. 741–749.
KDDKDD-2019-GaoPH #network #random
Conditional Random Field Enhanced Graph Convolutional Neural Networks (HG, JP, HH), pp. 276–284.
KDDKDD-2019-HanYZSLZ0K #identification #matrix #named #network
GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization (PH, PY, PZ, SS, YL0, JZ, XG0, PK), pp. 705–713.
KDDKDD-2019-HouCLCY #framework #learning #representation
A Representation Learning Framework for Property Graphs (YH, HC, CL, JC, MCY), pp. 65–73.
KDDKDD-2019-HuangSLH #network #random
Graph Recurrent Networks With Attributed Random Walks (XH, QS, YL, XH), pp. 732–740.
KDDKDD-2019-JiangZ00C0 #novel #representation
The Role of: A Novel Scientific Knowledge Graph Representation and Construction Model (TJ, TZ, BQ0, TL0, NVC, MJ0), pp. 1634–1642.
KDDKDD-2019-JiaSSB #learning
Graph-based Semi-Supervised & Active Learning for Edge Flows (JJ, MTS, SS, ARB), pp. 761–771.
KDDKDD-2019-LiHCSWZP #predict
Predicting Path Failure In Time-Evolving Graphs (JL, ZH, HC, JS, PW, JZ, LP), pp. 1279–1289.
KDDKDD-2019-LiuSPR #case study
Characterizing and Forecasting User Engagement with In-App Action Graph: A Case Study of Snapchat (YL, XS, LP, XR), pp. 2023–2031.
KDDKDD-2019-ParkKDZF #network #using
Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks (NP, AK, XLD, TZ, CF), pp. 596–606.
KDDKDD-2019-VermaZ #network
Stability and Generalization of Graph Convolutional Neural Networks (SV, ZLZ), pp. 1539–1548.
KDDKDD-2019-Wang00LC #named #network #recommendation
KGAT: Knowledge Graph Attention Network for Recommendation (XW, XH0, YC0, ML0, TSC), pp. 950–958.
KDDKDD-2019-WangLZ #adaptation #ambiguity #learning
Adaptive Graph Guided Disambiguation for Partial Label Learning (DBW, LL0, MLZ), pp. 83–91.
KDDKDD-2019-WangYCW00 #matrix #modelling #predict
Origin-Destination Matrix Prediction via Graph Convolution: a New Perspective of Passenger Demand Modeling (YW, HY, HC, TW, JX0, KZ0), pp. 1227–1235.
KDDKDD-2019-WangZZLZLW #network #recommendation
Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems (HW, FZ, MZ, JL, MZ, WL, ZW), pp. 968–977.
KDDKDD-2019-WuHX #classification #named #network
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification (JW, JH, JX), pp. 406–415.
KDDKDD-2019-WuYZXZPXA #kernel #random #scalability #using
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding (LW, IEHY, ZZ0, KX, LZ0, XP0, YX, CCA), pp. 1418–1428.
KDDKDD-2019-Xia #analysis #platform
Roll of Unified Graph Analysis Platforms (YX), p. 3179.
KDDKDD-2019-Yang #framework #named #network #platform
AliGraph: A Comprehensive Graph Neural Network Platform (HY), pp. 3165–3166.
KDDKDD-2019-YangRLC #named #recursion #sketching
NodeSketch: Highly-Efficient Graph Embeddings via Recursive Sketching (DY, PR, BL, PCM), pp. 1162–1172.
KDDKDD-2019-YinW #scalability
Scalable Graph Embeddings via Sparse Transpose Proximities (YY, ZW), pp. 1429–1437.
KDDKDD-2019-YoonHSF #approach #detection #performance
Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach (MY, BH, KS, CF), pp. 647–657.
KDDKDD-2019-YoshidaTK #learning #metric #mining
Learning Interpretable Metric between Graphs: Convex Formulation and Computation with Graph Mining (TY, IT, MK), pp. 1026–1036.
KDDKDD-2019-ZhangLTDYZGWSLW #named #scalability #towards
OAG: Toward Linking Large-scale Heterogeneous Entity Graphs (FZ, XL, JT, YD, PY, JZ, XG, YW, BS, RL, KW), pp. 2585–2595.
KDDKDD-2019-ZhangSHSC #network
Heterogeneous Graph Neural Network (CZ, DS, CH0, AS, NVC), pp. 793–803.
KDDKDD-2019-ZhuZ00 #network #robust
Robust Graph Convolutional Networks Against Adversarial Attacks (DZ, ZZ, PC0, WZ0), pp. 1399–1407.
KDDKDD-2019-ZugnerG #network #robust
Certifiable Robustness and Robust Training for Graph Convolutional Networks (DZ, SG), pp. 246–256.
MoDELSMoDELS-2019-BurV #estimation #query #runtime #towards
Towards WCET Estimation of Graph Queries@Run.time (MB, DV), pp. 233–238.
PLDIPLDI-2019-DhulipalaBS #streaming #using
Low-latency graph streaming using compressed purely-functional trees (LD, GEB, JS), pp. 918–934.
ASEASE-2019-DuCWLSC #named
CocoQa: Question Answering for Coding Conventions Over Knowledge Graphs (TD, JC, QW, WL, BS, YC), pp. 1086–1089.
ASEASE-2019-Gu00 #api #approach #kernel #named
CodeKernel: A Graph Kernel Based Approach to the Selection of API Usage Examples (XG, HZ0, SK0), pp. 590–601.
ASEASE-2019-Yu #empirical #python
Empirical Study of Python Call Graph (LY), pp. 1274–1276.
ESEC-FSEESEC-FSE-2019-Cetin #developer #identification #traceability #using
Identifying the most valuable developers using artifact traceability graphs (HAC), pp. 1196–1198.
ESEC-FSEESEC-FSE-2019-HiraoMIM #approach #code review #empirical #overview
The review linkage graph for code review analytics: a recovery approach and empirical study (TH, SM, AI, KM), pp. 578–589.
ESEC-FSEESEC-FSE-2019-KalhaugeP #dependence #reduction
Binary reduction of dependency graphs (CGK, JP), pp. 556–566.
ESEC-FSEESEC-FSE-2019-Papachristou #clustering #semantics
Software clusterings with vector semantics and the call graph (MP), pp. 1184–1186.
ESEC-FSEESEC-FSE-2019-Sulun #traceability #using
Suggesting reviewers of software artifacts using traceability graphs (ES), pp. 1250–1252.
ESEC-FSEESEC-FSE-2019-Vandenbogaerde #contract #design #framework
A graph-based framework for analysing the design of smart contracts (BV), pp. 1220–1222.
ICSE-2019-FanLLWNZL #analysis #android #learning #using
Graph embedding based familial analysis of Android malware using unsupervised learning (MF, XL, JL0, MW, CN, QZ, TL0), pp. 771–782.
ICSE-2019-NguyenNDNTH #fine-grained #mining #semantics
Graph-based mining of in-the-wild, fine-grained, semantic code change patterns (HAN, TNN, DD, SN, HT, MH), pp. 819–830.
SLESLE-2019-SeiferHLLS #empirical #java #open source #query
Empirical study on the usage of graph query languages in open source Java projects (PS, JH, ML, RL, SS), pp. 152–166.
ASPLOSASPLOS-2019-DathathriGHP #distributed #named
Phoenix: A Substrate for Resilient Distributed Graph Analytics (RD, GG, LH, KP), pp. 615–630.
ASPLOSASPLOS-2019-XuV0 #named #predict
PnP: Pruning and Prediction for Point-To-Point Iterative Graph Analytics (CX, KV, RG0), pp. 587–600.
ASPLOSASPLOS-2019-ZhangL0HLG #multi #named #performance
DiGraph: An Efficient Path-based Iterative Directed Graph Processing System on Multiple GPUs (YZ0, XL, HJ0, BH, HL, LG0), pp. 601–614.
CASECASE-2019-ChinnappaC
Average Consensus in Matrix-Weight-Balanced Digraphs (YC, DC), pp. 1637–1642.
CGOCGO-2019-SunBSB #reasoning #using
Reasoning about the Node.js Event Loop using Async Graphs (HS, DB, FS, WB), pp. 61–72.
FASEFASE-2019-GieseMSS #logic #metric
Metric Temporal Graph Logic over Typed Attributed Graphs (HG, MM, LS, SS0), pp. 282–298.
FASEFASE-2019-SchneiderLO #approach #incremental
A Logic-Based Incremental Approach to Graph Repair (SS0, LL, FO), pp. 151–167.
JCDLJCDL-2018-Lauscher0GSRADZ #database #library
Linked Open Citation Database: Enabling Libraries to Contribute to an Open and Interconnected Citation Graph (AL, KE0, LG, AS, STRR, SA, AD, PZ, AK), pp. 109–118.
EDMEDM-2018-AlsaadBGSZ #concept #dependence #mining
Mining MOOC Lecture Transcripts to Construct Concept Dependency Graphs (FA, AB, CG, HS, CZ).
ICSMEICSME-2018-LiLSXPLZ #api #mining
Improving API Caveats Accessibility by Mining API Caveats Knowledge Graph (HL, SL, JS, ZX, XP0, ML, XZ), pp. 183–193.
MSRMSR-2018-GeigerMPPNB #android #commit #dataset
A graph-based dataset of commit history of real-world Android apps (FXG, IM, LP, FP, DDN, AB), pp. 30–33.
SANERSANER-2018-HanLLXF #named #reasoning
DeepWeak: Reasoning common software weaknesses via knowledge graph embedding (ZH, XL0, HL, ZX, ZF0), pp. 456–466.
SANERSANER-2018-MoverSOC #corpus #framework #mining
Mining framework usage graphs from app corpora (SM, SS0, RBPO, BYEC), pp. 277–289.
SCAMSCAM-2018-AntalHTFG #case study #comparative #javascript #research
[Research Paper] Static JavaScript Call Graphs: A Comparative Study (GA, PH, ZT, RF, TG), pp. 177–186.
DLTDLT-2018-Crespi-Reghizzi #automaton
Deque Languages, Automata and Planar Graphs (SCR, PSP), pp. 243–255.
SEFMSEFM-2018-ArndtJMN #analysis
Graph-Based Shape Analysis Beyond Context-Freeness (HA, CJ, CM, TN0), pp. 271–286.
CoGCIG-2018-KraaijerKMR #game studies #generative #geometry
Geometry and Generation of a New Graph Planarity Game (RK, MJvK, WM, AvR), pp. 1–8.
FDGFDG-2018-SmithPV #generative #programming #set #using
Graph-based generation of action-adventure dungeon levels using answer set programming (TS0, JAP, AV), p. 10.
CIKMCIKM-2018-AkramiGHL
Re-evaluating Embedding-Based Knowledge Graph Completion Methods (FA, LG, WH, CL), pp. 1779–1782.
CIKMCIKM-2018-AslayNMG #evolution #mining
Mining Frequent Patterns in Evolving Graphs (ÇA, MAUN, GDFM, AG), pp. 923–932.
CIKMCIKM-2018-ChenWH #network #predict
Incorporating Corporation Relationship via Graph Convolutional Neural Networks for Stock Price Prediction (YC, ZW, XH), pp. 1655–1658.
CIKMCIKM-2018-ChuLXPLR0Z #e-commerce #optimisation #ranking
Deep Graph Embedding for Ranking Optimization in E-commerce (CC, ZL, BX, FP, CL, RR, QL0, JZ), pp. 2007–2015.
CIKMCIKM-2018-DingTZ #generative #learning
Semi-supervised Learning on Graphs with Generative Adversarial Nets (MD, JT, JZ), pp. 913–922.
CIKMCIKM-2018-DingZB0 #privacy #scalability
Privacy-Preserving Triangle Counting in Large Graphs (XD, XZ, ZB, HJ0), pp. 1283–1292.
CIKMCIKM-2018-GuanJWC #network
Shared Embedding Based Neural Networks for Knowledge Graph Completion (SG, XJ, YW, XC), pp. 247–256.
CIKMCIKM-2018-HeimannSSK #named #representation
REGAL: Representation Learning-based Graph Alignment (MH, HS, TS, DK), pp. 117–126.
CIKMCIKM-2018-HooiAEPJPF #detection #locality #named #online
ChangeDAR: Online Localized Change Detection for Sensor Data on a Graph (BH, LA, DE, AP, MJ, LTP, CF), pp. 507–516.
CIKMCIKM-2018-HusseinYC
Are Meta-Paths Necessary?: Revisiting Heterogeneous Graph Embeddings (RH, DY, PCM), pp. 437–446.
CIKMCIKM-2018-LeL #multi #similarity
Multiperspective Graph-Theoretic Similarity Measure (DDL, HWL), pp. 1223–1232.
CIKMCIKM-2018-LiuCYZLS #detection #network
Heterogeneous Graph Neural Networks for Malicious Account Detection (ZL, CC, XY, JZ, XL, LS), pp. 2077–2085.
CIKMCIKM-2018-LosterNEF #named
CurEx: A System for Extracting, Curating, and Exploring Domain-Specific Knowledge Graphs from Text (ML, FN, JE, BF), pp. 1883–1886.
CIKMCIKM-2018-NikolentzosV #kernel
Enhancing Graph Kernels via Successive Embeddings (GN, MV), pp. 1583–1586.
CIKMCIKM-2018-OhSL #learning #multi
Knowledge Graph Completion by Context-Aware Convolutional Learning with Multi-Hop Neighborhoods (BO, SS, KHL), pp. 257–266.
CIKMCIKM-2018-PapineniW
A Dynamical System on Bipartite Graphs (KP, PW), pp. 1479–1482.
CIKMCIKM-2018-SongZWTZJC #learning #named #rank
TGNet: Learning to Rank Nodes in Temporal Graphs (QS, BZ, YW, LAT, HZ, GJ, HC), pp. 97–106.
CIKMCIKM-2018-VazirgiannisMN #information retrieval #mining #named
GraphRep: Boosting Text Mining, NLP and Information Retrieval with Graphs (MV, FDM, GN), pp. 2295–2296.
CIKMCIKM-2018-WangYWJZZW #data mining #mining #named #scalability
AceKG: A Large-scale Knowledge Graph for Academic Data Mining (RW, YY, JW, YJ, YZ, WZ0, XW), pp. 1487–1490.
CIKMCIKM-2018-WangZWZLXG #named #recommendation
RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems (HW, FZ, JW, MZ, WL, XX, MG), pp. 417–426.
CIKMCIKM-2018-WuZA #classification #learning
A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification (XW, LZ, LA), pp. 87–96.
CIKMCIKM-2018-ZhangLNLX #multi #network
Multiresolution Graph Attention Networks for Relevance Matching (TZ, BL, DN, KL, YX), pp. 933–942.
ECIRECIR-2018-ZhangWXLS #precise #predict
Discriminative Path-Based Knowledge Graph Embedding for Precise Link Prediction (MZ, QW, WX, WL, SS), pp. 276–288.
ICMLICML-2018-AgrawalUB #modelling #scalability
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models (RA, CU, TB), pp. 89–98.
ICMLICML-2018-BacciuEM #approach #generative #markov
Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing (DB, FE, AM), pp. 304–313.
ICMLICML-2018-BargiacchiVRNH #coordination #learning #multi #problem
Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems (EB, TV, DMR, AN, HvH), pp. 491–499.
ICMLICML-2018-BojchevskiSZG #generative #named #random
NetGAN: Generating Graphs via Random Walks (AB, OS, DZ, SG), pp. 609–618.
ICMLICML-2018-CalandrielloKLV #learning #scalability
Improved Large-Scale Graph Learning through Ridge Spectral Sparsification (DC, IK, AL, MV), pp. 687–696.
ICMLICML-2018-ChenZS #network #probability #reduction
Stochastic Training of Graph Convolutional Networks with Variance Reduction (JC, JZ0, LS), pp. 941–949.
ICMLICML-2018-DaiKDSS #algorithm #learning
Learning Steady-States of Iterative Algorithms over Graphs (HD, ZK, BD, AJS, LS), pp. 1114–1122.
ICMLICML-2018-DaiLTHWZS
Adversarial Attack on Graph Structured Data (HD, HL, TT0, XH, LW, JZ0, LS), pp. 1123–1132.
ICMLICML-2018-DouikH #clustering #matrix #optimisation #probability #rank
Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering (AD, BH), pp. 1298–1307.
ICMLICML-2018-JinBJ #generative
Junction Tree Variational Autoencoder for Molecular Graph Generation (WJ, RB, TSJ), pp. 2328–2337.
ICMLICML-2018-LevinRMP
Out-of-sample extension of graph adjacency spectral embedding (KL, FRK, MWM, CEP), pp. 2981–2990.
ICMLICML-2018-LoukasV #approximate #scalability
Spectrally Approximating Large Graphs with Smaller Graphs (AL, PV), pp. 3243–3252.
ICMLICML-2018-RaguetL #algorithm
Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation (HR, LL), pp. 4244–4253.
ICMLICML-2018-RavivTDT
Gradient Coding from Cyclic MDS Codes and Expander Graphs (NR, RT, AD, IT), pp. 4302–4310.
ICMLICML-2018-Sanchez-Gonzalez #network #physics
Graph Networks as Learnable Physics Engines for Inference and Control (ASG, NH, JTS, JM, MAR, RH, PWB), pp. 4467–4476.
ICMLICML-2018-XuLTSKJ #learning #network #representation
Representation Learning on Graphs with Jumping Knowledge Networks (KX, CL, YT, TS, KiK, SJ), pp. 5449–5458.
ICMLICML-2018-YangKU #equivalence #learning
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions (KDY, AK, CU), pp. 5537–5546.
ICMLICML-2018-YouYRHL #generative #modelling #named
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models (JY, RY, XR, WLH, JL), pp. 5694–5703.
ICPRICPR-2018-AbreuFVBDNW #2d #image #modelling #segmentation
Model-based graph segmentation in 2-D fluorescence microsecopy images (AA, FXF, SV, PB, PD, BN, CW), pp. 3844–3849.
ICPRICPR-2018-BlumenthalDBBG #distance #edit distance #polynomial #problem
Quasimetric Graph Edit Distance as a Compact Quadratic Assignment Problem (DBB, ÉD, SB, LB, JG), pp. 934–939.
ICPRICPR-2018-CuiB00JH #hybrid #kernel #learning #network
A Deep Hybrid Graph Kernel Through Deep Learning Networks (LC, LB0, LR0, YW0, YJ0, ERH), pp. 1030–1035.
ICPRICPR-2018-CuradoELH18a #principle
Semi-supervised Graph Rewiring with the Dirichlet Principle (MC, FE, MAL, ERH), pp. 2172–2177.
ICPRICPR-2018-Do0V #multi
Knowledge Graph Embedding with Multiple Relation Projections (KD, TT0, SV), pp. 332–337.
ICPRICPR-2018-DornaikaTZ #flexibility #robust
Robust and Flexible Graph-based Semi-supervised Embedding (FD, YET, RZ), pp. 465–470.
ICPRICPR-2018-FariaS #analysis #approach #image
A Graph-based Approach for Static Ensemble Selection in Remote Sensing Image Analysis (FAF, SS), pp. 344–349.
ICPRICPR-2018-GengLH #novel #symmetry
A Novel Asymmetric Embedding Model for Knowledge Graph Completion (ZG, ZL, YH), pp. 290–295.
ICPRICPR-2018-JawadAH
Local Binary Patterns for Graph Characterization (MJ, FA, ERH), pp. 1241–1246.
ICPRICPR-2018-LiuRYXCY #image #network
Fully convolutional network and graph-based method for co-segmentation of retinal layer on macular OCT images (YL, GR, GY, XX, XC, YY), pp. 3081–3085.
ICPRICPR-2018-LuoZLW #clustering #image #learning
Graph Embedding-Based Ensemble Learning for Image Clustering (XL, LZ0, FL, BW), pp. 213–218.
ICPRICPR-2018-NiuS0 #learning
Enhancing Knowledge Graph Completion with Positive Unlabeled Learning (JN, ZS, WZ0), pp. 296–301.
ICPRICPR-2018-Pham0V #memory management #network #predict #process
Graph Memory Networks for Molecular Activity Prediction (TP, TT0, SV), pp. 639–644.
ICPRICPR-2018-QianWWL
Convolutional Features-Based CRF Graph Matching for Tracking of Densely Packed Cells (WQ, YW, XW, ML0), pp. 1797–1802.
ICPRICPR-2018-RibaFLF #learning #message passing #network
Learning Graph Distances with Message Passing Neural Networks (PR, AF0, JL0, AF), pp. 2239–2244.
ICPRICPR-2018-SantacruzS #distance #edit distance #generative #testing
Graph Edit Distance Testing through Synthetic Graphs Generation (PS, FS), pp. 572–577.
ICPRICPR-2018-Wang0H #evolution
Directed Graph Evolution from Euler-Lagrange Dynamics (JW, RCW0, ERH), pp. 448–453.
ICPRICPR-2018-XiaoDYLZW #adaptation #probability
Probabilistic Graph Embedding for Unsupervised Domain Adaptation (PX, BD, SY, XL, YZ, JW0), pp. 1283–1288.
ICPRICPR-2018-YeDW #classification
Graph-based Semi-supervised Classification with CRF and RNN (ZY, YD, FW), pp. 403–408.
ICPRICPR-2018-ZhangJCXP #approach #kernel #learning #network
Kernel-Weighted Graph Convolutional Network: A Deep Learning Approach for Traffic Forecasting (QZ, QJ, JC, SX, CP), pp. 1018–1023.
ICPRICPR-2018-ZhouXZH #higher-order #multi #online
Online Multi-Target Tracking with Tensor-Based High-Order Graph Matching (ZZ, JX, MZ, WH), pp. 1809–1814.
ICPRICPR-2018-ZhuMT #kernel #multi #retrieval
Multi-Kernel Supervised Hashing with Graph Regularization for Cross-Modal Retrieval (MZ, HM, JT), pp. 2717–2722.
ICPRICPR-2018-ZhuX #approximate #learning #scalability
Scalable Semi-Supervised Learning by Graph Construction with Approximate Anchors Embedding (HZ, MX), pp. 1331–1336.
KDDKDD-2018-ChenLZK #how
How LinkedIn Economic Graph Bonds Information and Product: Applications in LinkedIn Salary (XC, YL, LZ, KK), pp. 120–129.
KDDKDD-2018-Cohen-SteinerKS #approximate
Approximating the Spectrum of a Graph (DCS, WK, CS, GV), pp. 1263–1271.
KDDKDD-2018-Dong #challenge
Challenges and Innovations in Building a Product Knowledge Graph (XLD), p. 2869.
KDDKDD-2018-DuT #equation #mining #named #performance
FASTEN: Fast Sylvester Equation Solver for Graph Mining (BD, HT), pp. 1339–1347.
KDDKDD-2018-EswaranFGM #detection #named #streaming
SpotLight: Detecting Anomalies in Streaming Graphs (DE, CF, SG, NM), pp. 1378–1386.
KDDKDD-2018-GaoWJ #network #scalability
Large-Scale Learnable Graph Convolutional Networks (HG, ZW, SJ), pp. 1416–1424.
KDDKDD-2018-LeeRK #classification #using
Graph Classification using Structural Attention (JBL, RAR, XK), pp. 1666–1674.
KDDKDD-2018-LiHZ #predict
E-tail Product Return Prediction via Hypergraph-based Local Graph Cut (JL, JH, YZ), pp. 519–527.
KDDKDD-2018-LiuZZLYWY #interactive #proximity #semantics
Interactive Paths Embedding for Semantic Proximity Search on Heterogeneous Graphs (ZL, VWZ, ZZ, ZL, HY, MW, JY), pp. 1860–1869.
KDDKDD-2018-Park0 #effectiveness #named #performance #scalability
EvoGraph: An Effective and Efficient Graph Upscaling Method for Preserving Graph Properties (HP, MSK0), pp. 2051–2059.
KDDKDD-2018-ShenYXEBW0 #mobile #scalability
Mobile Access Record Resolution on Large-Scale Identifier-Linkage Graphs (XS, HY, WX, ME, JB, ZW, CW0), pp. 886–894.
KDDKDD-2018-TsitsulinMKBM #named
NetLSD: Hearing the Shape of a Graph (AT, DM, PK, AMB, EM), pp. 2347–2356.
KDDKDD-2018-WuZW #on the #using
On Discrimination Discovery and Removal in Ranked Data using Causal Graph (YW, LZ0, XW), pp. 2536–2544.
KDDKDD-2018-YingHCEHL #network #recommendation
Graph Convolutional Neural Networks for Web-Scale Recommender Systems (RY, RH, KC, PE, WLH, JL), pp. 974–983.
KDDKDD-2018-ZugnerAG #network
Adversarial Attacks on Neural Networks for Graph Data (DZ, AA, SG), pp. 2847–2856.
ECOOPECOOP-2018-GrechKS #analysis #performance #string
Efficient Reflection String Analysis via Graph Coloring (NG, GK, YS), p. 25.
OOPSLAOOPSLA-2018-ZhangYBKSA #domain-specific language #named
GraphIt: a high-performance graph DSL (YZ, MY, RB, SK, JS, SPA), p. 30.
PLDIPLDI-2018-DathathriGHDBDS #distributed #named
Gluon: a communication-optimizing substrate for distributed heterogeneous graph analytics (RD, GG, LH, HVD, AB, ND, MS, KP), pp. 752–768.
ASEASE-2018-GharibiTL #automation #generative #named #python #source code
Code2graph: automatic generation of static call graphs for Python source code (GG, RT, YL), pp. 880–883.
ASEASE-2018-HabibP #documentation #learning #thread #using
Is this class thread-safe? inferring documentation using graph-based learning (AH, MP), pp. 41–52.
ESEC-FSEESEC-FSE-2018-Zhou #debugging
Intelligent bug fixing with software bug knowledge graph (CZ), pp. 944–947.
ICSE-2018-KrieterTSSS
Propagating configuration decisions with modal implication graphs (SK, TT, SS, RS, GS), pp. 898–909.
ICSE-2018-SemerathNV #automation #consistency #generative #modelling
A graph solver for the automated generation of consistent domain-specific models (OS, ASN, DV), pp. 969–980.
ASPLOSASPLOS-2018-SabetQ0 #named
Tigr: Transforming Irregular Graphs for GPU-Friendly Graph Processing (AHNS, JQ, ZZ0), pp. 622–636.
ASPLOSASPLOS-2018-ZhangWZQHC #named #novel
Wonderland: A Novel Abstraction-Based Out-Of-Core Graph Processing System (MZ, YW, YZ, XQ, CH, KC), pp. 608–621.
CASECASE-2018-YangH #multi #on the
On a class of multi-input laplacian controllable graphs (PYY, SPH), pp. 310–315.
CGOCGO-2018-0003LJZW #concurrent #debugging #distributed #scalability
Scalable concurrency debugging with distributed graph processing (LZ0, XL, HJ0, JZ, QW), pp. 188–199.
CGOCGO-2018-DavisSO #data flow #metaprogramming
Transforming loop chains via macro dataflow graphs (ECD, MMS, CO), pp. 265–277.
FASEFASE-2018-BurSVV #cyber-physical #distributed #monitoring #query #runtime
Distributed Graph Queries for Runtime Monitoring of Cyber-Physical Systems (MB, GS, AV0, DV), pp. 111–128.
CAVCAV-2018-ArndtJKMN #exclamation #java #pointer #source code #verification
Let this Graph Be Your Witness! - An Attestor for Verifying Java Pointer Programs (HA, CJ, JPK, CM, TN0), pp. 3–11.
CAVCAV-2018-ChatterjeeHLOT #algorithm #markov #process
Symbolic Algorithms for Graphs and Markov Decision Processes with Fairness Objectives (KC, MH, VL, SO, VT), pp. 178–197.
TAPTAP-2018-HerdaTB #data flow #dependence #testing #using #verification
Using Dependence Graphs to Assist Verification and Testing of Information-Flow Properties (MH, SST, BB), pp. 83–102.
EDMEDM-2017-GrawemeyerWSHMP #learning #modelling #student #using
Using Graph-based Modelling to explore changes in students' affective states during exploratory learning tasks (BG, AW, SGS, WH, MM, AP).
EDMEDM-2017-LynchBXG #data mining #education #mining
Graph-based Educational Data Mining (CL, TB, LX, NG).
ICSMEICSME-2017-GoonetillekeMB #data transformation #dependence #evolution #multi
Graph Data Management of Evolving Dependency Graphs for Multi-versioned Codebases (OG, DM, BB), pp. 574–583.
SANERSANER-2017-ZhaoXKSLL #named
HDSKG: Harvesting domain specific knowledge graph from content of webpages (XZ, ZX, MAK, NS, JL0, SWL), pp. 56–67.
CIAACIAA-2017-BjorklundBE #on the #order
On the Regularity and Learnability of Ordered DAG Languages (HB, JB, PE), pp. 27–39.
DLTDLT-2017-Kitaev #formal method
A Comprehensive Introduction to the Theory of Word-Representable Graphs (SK), pp. 36–67.
HaskellHaskell-2017-Mokhov #algebra #functional
Algebraic graphs with class (functional pearl) (AM), pp. 2–13.
FDGFDG-2017-Abuzuraiq #clustering #constraints #generative #morphism #on the #using
On using graph partitioning with isomorphism constraint in procedural content generation (AMA), p. 10.
FDGFDG-2017-MazeikaW #3d #generative #modelling #named
Solusforge: controlling the generation of the 3D models with spatial relation graphs (JM, JW), p. 4.
FDGFDG-2017-MurrayMW #interactive #using
Proposal for analyzing player emotions in an interactive narrative using story intention graphs (JTM, MM, NWF), p. 4.
CIKMCIKM-2017-CaoZL #approach #approximate #distributed #effectiveness #mining #named #scalability
PMS: an Effective Approximation Approach for Distributed Large-scale Graph Data Processing and Mining (YC, YZ, JL), pp. 1999–2002.
CIKMCIKM-2017-CavallariZCCC #community #detection #learning
Learning Community Embedding with Community Detection and Node Embedding on Graphs (SC, VWZ, HC, KCCC, EC), pp. 377–386.
CIKMCIKM-2017-GaurBB #query #using
Tracking the Impact of Fact Deletions on Knowledge Graph Queries using Provenance Polynomials (GG, SJB, AB0), pp. 2079–2082.
CIKMCIKM-2017-Han0YZ #approach #assembly #keyword #query #rdf
Keyword Search on RDF Graphs - A Query Graph Assembly Approach (SH, LZ0, JXY, DZ0), pp. 227–236.
CIKMCIKM-2017-HuangCXCZ0 #ontology #perspective #visualisation
Ontology-based Graph Visualization for Summarized View (XH0, BC, JX, WKC, YZ, JL0), pp. 2115–2118.
CIKMCIKM-2017-HuangZLLZH #identification #named
KIEM: A Knowledge Graph based Method to Identify Entity Morphs (LH, LZ, SL, FL, YZ, SH), pp. 2111–2114.
CIKMCIKM-2017-HuCHFL #nondeterminism #on the
On Embedding Uncertain Graphs (JH, RC, ZH0, YF, SL), pp. 157–166.
CIKMCIKM-2017-HuPJL #classification #network
Graph Ladder Networks for Network Classification (RH, SP, JJ0, GL), pp. 2103–2106.
CIKMCIKM-2017-KansalS #database #scalability
A Scalable Graph-Coarsening Based Index for Dynamic Graph Databases (AK, FS), pp. 207–216.
CIKMCIKM-2017-KozawaAK #clustering #parallel
GPU-Accelerated Graph Clustering via Parallel Label Propagation (YK, TA, HK), pp. 567–576.
CIKMCIKM-2017-LiCM #pattern matching
Relaxing Graph Pattern Matching With Explanations (JL, YC0, SM0), pp. 1677–1686.
CIKMCIKM-2017-LiCY #learning #recommendation
Learning Graph-based Embedding For Time-Aware Product Recommendation (YL, WC, HY), pp. 2163–2166.
CIKMCIKM-2017-MaHLSYLR #analysis #clustering #multi
Multi-view Clustering with Graph Embedding for Connectome Analysis (GM, LH0, CTL, WS, PSY, ADL, ABR), pp. 127–136.
CIKMCIKM-2017-Moon0S #learning
Learning Entity Type Embeddings for Knowledge Graph Completion (CM, PJ0, NFS), pp. 2215–2218.
CIKMCIKM-2017-NamakiWSLG
Discovering Graph Temporal Association Rules (MHN, YW, QS, PL, TG), pp. 1697–1706.
CIKMCIKM-2017-PalU #correlation
Enhancing Knowledge Graph Completion By Embedding Correlations (SP, JU), pp. 2247–2250.
CIKMCIKM-2017-RongC #dependence
Minimizing Dependence between Graphs (YR, HC), pp. 1827–1836.
CIKMCIKM-2017-SathanurCJP #network #simulation
When Labels Fall Short: Property Graph Simulation via Blending of Network Structure and Vertex Attributes (AVS, SC, CAJ, SP), pp. 2287–2290.
CIKMCIKM-2017-SeoK #algorithm #clustering #named #performance #scalability
pm-SCAN: an I/O Efficient Structural Clustering Algorithm for Large-scale Graphs (JHS, MHK), pp. 2295–2298.
CIKMCIKM-2017-ShiGQZ
Knowledge Graph Embedding with Triple Context (JS, HG, GQ, ZZ), pp. 2299–2302.
CIKMCIKM-2017-SrivastavaD #retrieval #semantics #similarity
Soft Seeded SSL Graphs for Unsupervised Semantic Similarity-based Retrieval (AS, MD), pp. 2315–2318.
CIKMCIKM-2017-TanZW #learning #representation #scalability
Representation Learning of Large-Scale Knowledge Graphs via Entity Feature Combinations (ZT, XZ0, WW0), pp. 1777–1786.
CIKMCIKM-2017-TayTPH #multi #network #predict
Multi-Task Neural Network for Non-discrete Attribute Prediction in Knowledge Graphs (YT, LAT, MCP, SCH), pp. 1029–1038.
CIKMCIKM-2017-WangCL #twitter #using
Using Knowledge Graphs to Explain Entity Co-occurrence in Twitter (YW, MJC, YFL), pp. 2351–2354.
CIKMCIKM-2017-WangPLZJ #clustering #named
MGAE: Marginalized Graph Autoencoder for Graph Clustering (CW, SP, GL, XZ, JJ0), pp. 889–898.
CIKMCIKM-2017-WangQPZX #semantics
Semantic Annotation for Places in LBSN through Graph Embedding (YW, ZQ, JP0, YZ0, JX), pp. 2343–2346.
CIKMCIKM-2017-XuWXQ #classification #network #recursion
Attentive Graph-based Recursive Neural Network for Collective Vertex Classification (QX, QW, CX, LQ), pp. 2403–2406.
CIKMCIKM-2017-YangWLZL #network
From Properties to Links: Deep Network Embedding on Incomplete Graphs (DY, SW, CL, XZ0, ZL), pp. 367–376.
CIKMCIKM-2017-ZhangH #ambiguity #network #using
Name Disambiguation in Anonymized Graphs using Network Embedding (BZ, MAH), pp. 1239–1248.
CIKMCIKM-2017-ZhangXKZ #interactive #learning
Learning Node Embeddings in Interaction Graphs (YZ, YX, XK, YZ), pp. 397–406.
CIKMCIKM-2017-ZhengC0YZ #natural language
Natural Language Question/Answering: Let Users Talk With The Knowledge Graph (WZ, HC, LZ0, JXY, KZ), pp. 217–226.
ECIRECIR-2017-GangulyP #named #representation
Paper2vec: Combining Graph and Text Information for Scientific Paper Representation (SG, VP), pp. 383–395.
ICMLICML-2017-FeldmanOR #network #summary
Coresets for Vector Summarization with Applications to Network Graphs (DF, SO, DR), pp. 1117–1125.
ICMLICML-2017-HornakovaLA #analysis #multi #optimisation
Analysis and Optimization of Graph Decompositions by Lifted Multicuts (AH, JHL, BA), pp. 1539–1548.
ICMLICML-2017-KhasanovaF #invariant #learning #representation
Graph-based Isometry Invariant Representation Learning (RK, PF), pp. 1847–1856.
ICMLICML-2017-KocaogluDV #learning
Cost-Optimal Learning of Causal Graphs (MK, AD, SV), pp. 1875–1884.
ICMLICML-2017-LeeHGJC #random
Bayesian inference on random simple graphs with power law degree distributions (JL, CH, ZG, LFJ, SC), pp. 2004–2013.
ICMLICML-2017-LeiJBJ #architecture #kernel #sequence
Deriving Neural Architectures from Sequence and Graph Kernels (TL0, WJ, RB, TSJ), pp. 2024–2033.
ICMLICML-2017-TrivediDWS #named #reasoning
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs (RT, HD, YW0, LS), pp. 3462–3471.
KDDKDD-2017-ChoiBSSS #learning #named #representation
GRAM: Graph-based Attention Model for Healthcare Representation Learning (EC, MTB, LS, WFS, JS), pp. 787–795.
KDDKDD-2017-MalloyBAKJ #internet
Internet Device Graphs (MM, PB, ECA, JK, AJ), pp. 1913–1921.
KDDKDD-2017-TillmanMBG
Construction of Directed 2K Graphs (BT, AM, CTB, MG), pp. 1115–1124.
KDDKDD-2017-YinBLG #clustering #higher-order
Local Higher-Order Graph Clustering (HY, ARB, JL, DFG), pp. 555–564.
KDDKDD-2017-ZhangWLTL #clustering #heuristic
Graph Edge Partitioning via Neighborhood Heuristic (CZ, FW, QL, ZGT, ZL), pp. 605–614.
KDDKDD-2017-ZhangWP #visualisation
Visualizing Attributed Graphs via Terrain Metaphor (YZ, YW, SP0), pp. 1325–1334.
KDDKDD-2017-ZhouZYATDH #algorithm
A Local Algorithm for Structure-Preserving Graph Cut (DZ, SZ, MYY, SA, HT, HD, JH), pp. 655–664.
ICMTICMT-2017-SemerathV #constraints #evaluation #modelling
Graph Constraint Evaluation over Partial Models by Constraint Rewriting (OS, DV), pp. 138–154.
OOPSLAOOPSLA-2017-PapadakisB0AH #named
Seam: provably safe local edits on graphs (MP, GLB, RS0, AA, PH), p. 29.
AdaEuropeAdaEurope-2017-MedinaBP #scheduling
Directed Acyclic Graph Scheduling for Mixed-Criticality Systems (RM0, EB, LP), pp. 217–232.
AdaEuropeAdaEurope-2017-MohaqeqiA0 #ada #execution #semantics
An Executable Semantics for Synchronous Task Graphs: From SDRT to Ada (MM, JA, WY0), pp. 137–152.
ESEC-FSEESEC-FSE-2017-MaAXLZLZ #algorithm #machine learning #named
LAMP: data provenance for graph based machine learning algorithms through derivative computation (SM, YA, ZX, WCL, JZ, YL, XZ0), pp. 786–797.
ESEC-FSEESEC-FSE-2017-YuanXXPZ #android #execution #named
RunDroid: recovering execution call graphs for Android applications (YY, LX, XX, AP, HZ), pp. 949–953.
ASPLOSASPLOS-2017-VoraGX #approximate #named #performance #streaming
KickStarter: Fast and Accurate Computations on Streaming Graphs via Trimmed Approximations (KV, RG0, G(X), pp. 237–251.
ASPLOSASPLOS-2017-VoraTGH #distributed #named
CoRAL: Confined Recovery in Distributed Asynchronous Graph Processing (KV, CT0, RG0, ZH), pp. 223–236.
ASPLOSASPLOS-2017-WangHZXS #analysis #interprocedural #named #scalability
Graspan: A Single-machine Disk-based Graph System for Interprocedural Static Analyses of Large-scale Systems Code (KW0, AH0, ZZ0, G(X, AAS), pp. 389–404.
CASECASE-2017-0013YG #image #optimisation #using
Accurate image mosaicing for bridge deck using graph optimization with GPS data (FL0, JY, NG), pp. 1090–1095.
CASECASE-2017-HeLG #optimisation
Optimization of deterministic timed weighted marked graphs (ZH, ZL, AG), pp. 956–957.
CASECASE-2017-WuWW #algorithm #estimation #multi
A t-level driven search for estimation of distribution algorithm in solving task graph allocation to multiprocessors (CW, LW0, JW), pp. 630–635.
FASEFASE-2017-SchneiderLO #generative
Symbolic Model Generation for Graph Properties (SS0, LL, FO), pp. 226–243.
CSLCSL-2017-Grussien #polynomial
Capturing Logarithmic Space and Polynomial Time on Chordal Claw-Free Graphs (BG), p. 19.
CSEETCSEET-2016-WeiDCS #concept #education #framework #modelling #requirements #uml
A Conceptual Graphs Framework for Teaching UML Model-Based Requirements Acquisition (BW, HSD, EC, CS), pp. 71–75.
EDMEDM-2016-ChaplotYCK #automation #data-driven #induction
Data-driven Automated Induction of Prerequisite Structure Graphs (DSC, YY, JGC, KRK), pp. 318–323.
EDMEDM-2016-ChenGT #modelling #student
Joint Discovery of Skill Prerequisite Graphs and Student Models (YC, JPGB, JT0), pp. 46–53.
EDMEDM-2016-JiangG #approach #contest #mining #on the
On Competition for Undergraduate Co-op Placements: A Graph Mining Approach (YHJ, LG), pp. 394–399.
SCAMSCAM-2016-LossingGI #c #compilation #concept #dependence #text-to-text
Effects Dependence Graph: A Key Data Concept for C Source-to-Source Compilers (NL, PG, FI), pp. 167–176.
SCAMSCAM-2016-MuscoMP #fault #locality
Mutation-Based Graph Inference for Fault Localization (VM, MM, PP), pp. 97–106.
DLTDLT-2016-Duck #automaton #infinity #logic
Weighted Automata and Logics on Infinite Graphs (SD), pp. 151–163.
HaskellHaskell-2016-DexterLC #haskell #lazy evaluation
Lazy graph processing in Haskell (PD, YDL, KC), pp. 182–192.
ICFP-2016-EmotoMHMI #domain-specific language #exclamation #functional
Think like a vertex, behave like a function! a functional DSL for vertex-centric big graph processing (KE, KM, ZH, AM, HI), pp. 200–213.
CIKMCIKM-2016-AguinagaPCW #graph grammar
Growing Graphs from Hyperedge Replacement Graph Grammars (SA, RP, DC0, TW), pp. 469–478.
CIKMCIKM-2016-AlabdulmohsinHS #detection
Content-Agnostic Malware Detection in Heterogeneous Malicious Distribution Graph (IMA, YH, YS, XZ0), pp. 2395–2400.
CIKMCIKM-2016-Balaneshinkordan #concept #query #using
Sequential Query Expansion using Concept Graph (SB, AK), pp. 155–164.
CIKMCIKM-2016-BandyopadhyayFC #incremental #scalability #sketching
Topological Graph Sketching for Incremental and Scalable Analytics (BB, DF, AC, SP0), pp. 1231–1240.
CIKMCIKM-2016-ChenLYWLZ #keyword #multi #performance #query
Efficient Batch Processing for Multiple Keyword Queries on Graph Data (LC, CL, XY0, BW0, JL, RZ0), pp. 1261–1270.
CIKMCIKM-2016-ChodpathumwanAT #database #independence #representation #similarity #towards
Towards Representation Independent Similarity Search Over Graph Databases (YC, AA, AT, YS), pp. 2233–2238.
CIKMCIKM-2016-EtemadiLT #estimation #performance #scalability
Efficient Estimation of Triangles in Very Large Graphs (RE, JL, YHT), pp. 1251–1260.
CIKMCIKM-2016-HoLSKDWZS #algorithm #behaviour #distributed #scalability
A Distributed Graph Algorithm for Discovering Unique Behavioral Groups from Large-Scale Telco Data (QH, WL, ES, SK, TAD, JW, ICZ, ASN), pp. 1353–1362.
CIKMCIKM-2016-HuangSLMH #data transformation #named
TGraph: A Temporal Graph Data Management System (HH, JS, XL, SM0, JH), pp. 2469–2472.
CIKMCIKM-2016-HuWCLF #query #scalability
Querying Minimal Steiner Maximum-Connected Subgraphs in Large Graphs (JH, XW, RC, SL, YF), pp. 1241–1250.
CIKMCIKM-2016-JoHJBK #locality
Data Locality in Graph Engines: Implications and Preliminary Experimental Results (YYJ, JH, MHJ, JGB, SWK), pp. 1885–1888.
CIKMCIKM-2016-KangPYC #recommendation
Top-N Recommendation on Graphs (ZK, CP, MY, QC), pp. 2101–2106.
CIKMCIKM-2016-KargarGS #effectiveness #keyword #named
eGraphSearch: Effective Keyword Search in Graphs (MK, LG, JS), pp. 2461–2464.
CIKMCIKM-2016-KimXO #composition #incremental #probability
Probabilistic Knowledge Graph Construction: Compositional and Incremental Approaches (DK0, LX, CSO), pp. 2257–2262.
CIKMCIKM-2016-LiakosPD #distributed #novel
Memory-Optimized Distributed Graph Processing through Novel Compression Techniques (PL, KP, AD), pp. 2317–2322.
CIKMCIKM-2016-LiCL #approximate #query #using
Approximating Graph Pattern Queries Using Views (JL, YC0, XL), pp. 449–458.
CIKMCIKM-2016-LiuZCC #detection #statistics #topic
Graph Topic Scan Statistic for Spatial Event Detection (YL, BZ, FC0, DWC), pp. 489–498.
CIKMCIKM-2016-LiuZGF #adaptation #named #online
GiraphAsync: Supporting Online and Offline Graph Processing via Adaptive Asynchronous Message Processing (YL, CZ, JG, ZF), pp. 479–488.
CIKMCIKM-2016-VesdapuntG #api #social
Updating an Existing Social Graph Snapshot via a Limited API (NV, HGM), pp. 1693–1702.
CIKMCIKM-2016-WangWZ #distributed #partial evaluation #performance #query #rdf #using
Efficient Distributed Regular Path Queries on RDF Graphs Using Partial Evaluation (XW0, JW, XZ), pp. 1933–1936.
CIKMCIKM-2016-XieYWXCW #learning #recommendation
Learning Graph-based POI Embedding for Location-based Recommendation (MX, HY, HW, FX, WC, SW), pp. 15–24.
CIKMCIKM-2016-ZhengW #learning #multi
Graph-Based Multi-Modality Learning for Clinical Decision Support (ZZ, XW0), pp. 1945–1948.
ECIRECIR-2016-AkerKBPBHG #approach #clustering #online #topic
A Graph-Based Approach to Topic Clustering for Online Comments to News (AA, EK, ARB, MLP, EB, MH, RJG), pp. 15–29.
ECIRECIR-2016-Balaneshinkordan #comparison #empirical #query
An Empirical Comparison of Term Association and Knowledge Graphs for Query Expansion (SB, AK), pp. 761–767.
ECIRECIR-2016-ChenJYYZ #modelling #probability #semantics #topic
Probabilistic Topic Modelling with Semantic Graph (LC0, JMJ, HY, FY, HZ), pp. 240–251.
ICMLICML-2016-ChenKST #community #locality
Community Recovery in Graphs with Locality (YC0, GMK, CS, DT), pp. 689–698.
ICMLICML-2016-CohenHK #feedback #learning #online
Online Learning with Feedback Graphs Without the Graphs (AC, TH, TK), pp. 811–819.
ICMLICML-2016-NiepertAK #learning #network
Learning Convolutional Neural Networks for Graphs (MN, MA, KK), pp. 2014–2023.
ICMLICML-2016-YangCS #learning
Revisiting Semi-Supervised Learning with Graph Embeddings (ZY, WWC, RS), pp. 40–48.
ICPRICPR-2016-AytekinIKG #segmentation
Salient object segmentation based on linearly combined affinity graphs (ÇA, AI, SK, MG), pp. 3769–3774.
ICPRICPR-2016-Bai0CH16a #matrix #novel
A novel entropy-based graph signature from the average mixing matrix (LB0, LR0, LC, ERH), pp. 1339–1344.
ICPRICPR-2016-BaiCWJ0H #classification #clustering #kernel
Shape classification with a vertex clustering graph kernel (LB0, LC, YW0, XJ0, XB0, ERH), pp. 2634–2639.
ICPRICPR-2016-BougleuxGB #distance #edit distance #polynomial
Graph edit distance as a quadratic program (SB, BG, LB), pp. 1701–1706.
ICPRICPR-2016-GligorijevicPZ #community #detection #multi
Fusion and community detection in multi-layer graphs (VG, YP, SZ), pp. 1327–1332.
ICPRICPR-2016-HouXX0 #classification #learning
Semi-supervised learning competence of classifiers based on graph for dynamic classifier selection (CH, YX, ZX, JS0), pp. 3650–3654.
ICPRICPR-2016-JavedJMB #modelling
Motion-Aware Graph Regularized RPCA for background modeling of complex scenes (SJ, SKJ, AM, TB), pp. 120–125.
ICPRICPR-2016-Kamkar0LPV #predict #using
Stable clinical prediction using graph support vector machines (IK, SG0, CL0, DQP, SV), pp. 3332–3337.
ICPRICPR-2016-KooliB #documentation #recognition
Inexact graph matching for entity recognition in OCRed documents (NK, AB), pp. 4071–4076.
ICPRICPR-2016-MiyazakiO #recognition
Graph model boosting for structural data recognition (TM, SO), pp. 1707–1712.
ICPRICPR-2016-OhY #algorithm #learning
Enhancing label inference algorithms considering vertex importance in graph-based semi-supervised learning (BO, JY), pp. 1671–1676.
ICPRICPR-2016-OrueG #process #recognition #using
Face recognition using activities of directed graphs in spatial pyramid (JPMO, WNG), pp. 3162–3167.
ICPRICPR-2016-RaiNCD #clustering #multi #using
Partial Multi-View Clustering using Graph Regularized NMF (NR, SN, SC, OD), pp. 2192–2197.
ICPRICPR-2016-Robles-KellyW #image #using
Semi-supervised image labelling using barycentric graph embeddings (ARK, RW), pp. 1518–1523.
ICPRICPR-2016-WuZLMS #named #novel
EvaToon: A novel graph matching system for evaluating cartoon drawings (YW, XZ, TL, GM, LS), pp. 1119–1124.
ICPRICPR-2016-YeWH #generative #using
Analyzing graph time series using a generative model (CY, RCW0, ERH), pp. 3338–3343.
ICPRICPR-2016-ZhengTZW #estimation #reduction
Maximal level estimation and unbalance reduction for graph signal downsampling (XZ, YYT, JZ0, PSPW), pp. 3922–3926.
ICPRICPR-2016-ZhugeHNY #clustering #feature model #using
Unsupervised feature extraction using a learned graph with clustering structure (WZ, CH, FN, DY), pp. 3597–3602.
KDDKDD-2016-AkibaY #scalability #sketching
Compact and Scalable Graph Neighborhood Sketching (TA, YY), pp. 685–694.
KDDKDD-2016-DhulipalaKKOPS #recursion
Compressing Graphs and Indexes with Recursive Graph Bisection (LD, IK, BK, GO, SP, AS), pp. 1535–1544.
KDDKDD-2016-HooiSBSSF #bound #named
FRAUDAR: Bounding Graph Fraud in the Face of Camouflage (BH, HAS, AB, NS, KS, CF), pp. 895–904.
KDDKDD-2016-MaccioniA #pattern matching #scalability
Scalable Pattern Matching over Compressed Graphs via Dedensification (AM, DJA), pp. 1755–1764.
KDDKDD-2016-ManzoorMA #detection #performance #streaming
Fast Memory-efficient Anomaly Detection in Streaming Heterogeneous Graphs (EAM, SMM, LA), pp. 1035–1044.
KDDKDD-2016-NandiMADB #control flow #detection #execution #mining #using
Anomaly Detection Using Program Control Flow Graph Mining From Execution Logs (AN, AM, SA, GBD, SB), pp. 215–224.
KDDKDD-2016-OuCPZ0 #symmetry #transitive
Asymmetric Transitivity Preserving Graph Embedding (MO, PC0, JP, ZZ, WZ0), pp. 1105–1114.
KDDKDD-2016-RiondatoU #approximate #named
ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages (MR, EU), pp. 1145–1154.
KDDKDD-2016-SilvaDBSS
Graph Wavelets via Sparse Cuts (AS, XHD, PB, AKS, AS), pp. 1175–1184.
KDDKDD-2016-WangNH #clustering #matrix #probability
Structured Doubly Stochastic Matrix for Graph Based Clustering: Structured Doubly Stochastic Matrix (XW, FN, HH), pp. 1245–1254.
KDDKDD-2016-ZhangLG #approximate #personalisation #rank
Approximate Personalized PageRank on Dynamic Graphs (HZ, PL, AG), pp. 1315–1324.
ICMTICMT-2016-StrueberPA #clone detection #detection #model transformation #transformation language
Clone Detection for Graph-Based Model Transformation Languages (DS, JP, VA), pp. 191–206.
MoDELSMoDELS-2016-Garcia-Dominguez #integration #modelling #tool support
Integration of a graph-based model indexer in commercial modelling tools (AGD, KB, DSK, MAAdS, AA, AB), pp. 340–350.
MoDELSMoDELS-2016-SzarnyasKSV #evaluation #metric #modelling #multi #towards
Towards the characterization of realistic models: evaluation of multidisciplinary graph metrics (GS, ZK, ÁS, DV), pp. 87–94.
ECOOPECOOP-2016-HarkesGV #incremental #named #persistent
IceDust: Incremental and Eventual Computation of Derived Values in Persistent Object Graphs (DH, DMG, EV), p. 26.
OOPSLAOOPSLA-2016-PaiP #algorithm #compilation #optimisation #throughput
A compiler for throughput optimization of graph algorithms on GPUs (SP, KP), pp. 1–19.
OOPSLAOOPSLA-2016-PetrashkoULO #morphism #parametricity #polymorphism
Call graphs for languages with parametric polymorphism (DP, VU, OL, MO), pp. 394–409.
AdaEuropeAdaEurope-2016-MohaqeqiAY #analysis #data flow #modelling #realtime #using
Modeling and Analysis of Data Flow Graphs Using the Digraph Real-Time Task Model (MM, JA, WY0), pp. 15–29.
PEPMPEPM-2016-AntwerpenNTVW #analysis #constraints #semantics
A constraint language for static semantic analysis based on scope graphs (HvA, PN, APT, EV, GW), pp. 49–60.
SASSAS-2016-GharatKM #analysis #points-to #using
Flow- and Context-Sensitive Points-To Analysis Using Generalized Points-To Graphs (PMG, UPK, AM), pp. 212–236.
ASEASE-2016-Mougouei #dependence #integer #programming #requirements #using
Factoring requirement dependencies in software requirement selection using graphs and integer programming (DM), pp. 884–887.
FSEFSE-2016-ReifEHLM #java #library
Call graph construction for Java libraries (MR, ME, BH, JL, MM), pp. 474–486.
CASECASE-2016-SyJDD #clustering #detection
Graph-based clustering for detecting frequent patterns in event log data (ES, SAJ, AD, YD0), pp. 972–977.
CCCC-2016-NgY #concurrent #detection #synthesis
Static deadlock detection for concurrent go by global session graph synthesis (NN, NY), pp. 174–184.
CGOCGO-2016-NguyenL #multi #platform
Communication-aware mapping of stream graphs for multi-GPU platforms (DN0, JL), pp. 94–104.
FASEFASE-2016-CorrodiHP #concurrent #semantics #source code
A Graph-Based Semantics Workbench for Concurrent Asynchronous Programs (CC, AH, CMP), pp. 31–48.
FASEFASE-2016-WangLW #co-evolution
The Influences of Edge Instability on Change Propagation and Connectivity in Call Graphs (LW, HL, XW), pp. 197–213.
CAVCAV-2016-SevegnaniC #analysis #named
BigraphER: Rewriting and Analysis Engine for Bigraphs (MS, MC), pp. 494–501.
CSLCSL-2016-EickmeyerK #first-order #invariant #logic
Successor-Invariant First-Order Logic on Graphs with Excluded Topological Subgraphs (KE, KiK), p. 15.
CSLCSL-2016-Elberfeld
Context-Free Graph Properties via Definable Decompositions (ME), p. 16.
IJCARIJCAR-2016-DochertyP #logic
Intuitionistic Layered Graph Logic (SD, DJP), pp. 469–486.
HTHT-2015-SongFGWCZ #microblog #word
Build Emotion Lexicon from Microblogs by Combining Effects of Seed Words and Emoticons in a Heterogeneous Graph (KS, SF, WG, DW, LC, CZ), pp. 283–292.
PODSPODS-2015-GuhaMT
Vertex and Hyperedge Connectivity in Dynamic Graph Streams (SG, AM, DT), pp. 241–247.
PODSPODS-2015-MunroNV #data type #documentation
Dynamic Data Structures for Document Collections and Graphs (JIM, YN, JSV), pp. 277–289.
PODSPODS-2015-PraveenS #how #question
Defining Relations on Graphs: How Hard is it in the Presence of Node Partitions? (MP, BS), pp. 159–172.
SIGMODSIGMOD-2015-ArmenatzoglouPN #approach #clustering #game studies #multi #realtime #social
Real-Time Multi-Criteria Social Graph Partitioning: A Game Theoretic Approach (NA, HP, VN, DP, CS), pp. 1617–1628.
SIGMODSIGMOD-2015-HuangFL
Minimum Spanning Trees in Temporal Graphs (SH, AWCF, RL), pp. 419–430.
SIGMODSIGMOD-2015-PerezSBPRSL #interactive #named
Ringo: Interactive Graph Analytics on Big-Memory Machines (YP, RS, AB, RP, MR, PS, JL), pp. 1105–1110.
SIGMODSIGMOD-2015-ShinJSK #approach #named #random #scalability
BEAR: Block Elimination Approach for Random Walk with Restart on Large Graphs (KS, JJ, LS, UK), pp. 1571–1585.
SIGMODSIGMOD-2015-SunFSKHX #named #performance
SQLGraph: An Efficient Relational-Based Property Graph Store (WS, AF, KS, AK, GH, GTX), pp. 1887–1901.
SIGMODSIGMOD-2015-YuanMYG #algorithm
Updating Graph Indices with a One-Pass Algorithm (DY, PM, HY, CLG), pp. 1903–1916.
SIGMODSIGMOD-2015-ZhangCPSX #statistics #using
Private Release of Graph Statistics using Ladder Functions (JZ, GC, CMP, DS, XX), pp. 731–745.
SIGMODSIGMOD-2015-ZhengZLYSZ #approach #how #nondeterminism #rdf #similarity
How to Build Templates for RDF Question/Answering: An Uncertain Graph Similarity Join Approach (WZ, LZ, XL, JXY, SS, DZ), pp. 1809–1824.
VLDBVLDB-2015-CebiricGM #query #rdf #summary
Query-Oriented Summarization of RDF Graphs (SC, FG, IM), pp. 2012–2023.
VLDBVLDB-2015-ChingEKLM
One Trillion Edges: Graph Processing at Facebook-Scale (AC, SE, MK, DL, SM), pp. 1804–1815.
VLDBVLDB-2015-ChodpathumwanAT #independence #named #representation #towards
Universal-DB: Towards Representation Independent Graph Analytics (YC, AA, AT, YS), pp. 2016–2027.
VLDBVLDB-2015-FanFTD
Keys for Graphs (WF, ZF, CT, XLD), pp. 1590–1601.
VLDBVLDB-2015-FanWWX
Association Rules with Graph Patterns (WF, XW, YW, JX), pp. 1502–1513.
VLDBVLDB-2015-HanD #execution #parallel
Giraph Unchained: Barrierless Asynchronous Parallel Execution in Pregel-like Graph Processing Systems (MH, KD), pp. 950–961.
VLDBVLDB-2015-JayaramGL #interactive #interface #named #query #visual notation
VIIQ: Auto-Suggestion Enabled Visual Interface for Interactive Graph Query Formulation (NJ, SG, CL), pp. 1940–1951.
VLDBVLDB-2015-KazemiHG
Growing a Graph Matching from a Handful of Seeds (EK, SHH, MG), pp. 1010–1021.
VLDBVLDB-2015-KhanC #modelling #nondeterminism #on the #query
On Uncertain Graphs Modeling and Queries (AK, LC), pp. 2042–2053.
VLDBVLDB-2015-KoutraJNF #interactive #mining #named #scalability #visualisation
Perseus: An Interactive Large-Scale Graph Mining and Visualization Tool (DK, DJ, YN, CF), pp. 1924–1935.
VLDBVLDB-2015-LiuLYXW #independence #set #towards
Towards Maximum Independent Sets on Massive Graphs (YL, JL, HY, XX, ZW), pp. 2122–2133.
VLDBVLDB-2015-MargoS #distributed #scalability
A Scalable Distributed Graph Partitioner (DWM, MIS), pp. 1478–1489.
VLDBVLDB-2015-MitliagkasBDC #approximate #exclamation #performance #rank
FrogWild! — Fast PageRank Approximations on Graph Engines (IM, MB, AGD, CC), pp. 874–885.
VLDBVLDB-2015-RenW #morphism #scalability
Exploiting Vertex Relationships in Speeding up Subgraph Isomorphism over Large Graphs (XR, JW), pp. 617–628.
VLDBVLDB-2015-ShaoC0LX #framework #performance #scalability #similarity
An Efficient Similarity Search Framework for SimRank over Large Dynamic Graphs (YS, BC, LC, ML, XX), pp. 838–849.
VLDBVLDB-2015-ShiokawaFO #algorithm #clustering #performance #scalability
SCAN++: Efficient Algorithm for Finding Clusters, Hubs and Outliers on Large-scale Graphs (HS, YF, MO), pp. 1178–1189.
VLDBVLDB-2015-SundaramSPDAV0D #effectiveness #named #performance
GraphMat: High performance graph analytics made productive (NS, NS, MMAP, SD, MJA, SGV, DD, PD), pp. 1214–1225.
VLDBVLDB-2015-Xirogiannopoulos #named #relational
GraphGen: Exploring Interesting Graphs in Relational Data (KX, UK, AD), pp. 2032–2043.
VLDBVLDB-2015-ZhangC0 #approach #distributed #set
Bonding Vertex Sets Over Distributed Graph: A Betweenness Aware Approach (XZ, HC, LC), pp. 1418–1429.
VLDBVLDB-2015-ZhouLLZ #named #optimisation #performance
GraphTwist: Fast Iterative Graph Computation with Two-tier Optimizations (YZ, LL, KL, QZ), pp. 1262–1273.
EDMEDM-2015-JohnPM #detection #problem #question #semantics #similarity #word
Semantic Similarity Graphs of Mathematics Word Problems: Can Terminology Detection Help? (RJLJ, RJP, TSM), pp. 452–455.
EDMEDM-2015-SiemensBG #learning
Personal Knowledge/Learning Graph (GS, RSB, DG), p. 5.
MSRMSR-2015-SchumacherA #framework
An Enhanced Graph-Based Infrastructure for Software Search Engines (MS, CA), pp. 386–390.
SANERSANER-2015-Abi-AntounWKGR #impact analysis
Impact analysis based on a global hierarchical Object Graph (MAA, YW, EK, AG, VR), pp. 221–230.
SANERSANER-2015-BezemerPG #comprehension #difference #performance #using
Understanding software performance regressions using differential flame graphs (CPB, JP, BG), pp. 535–539.
SANERSANER-2015-LaverdiereBM #analysis #composition #using
Taint analysis of manual service compositions using Cross-Application Call Graphs (MAL, BJB, EM), pp. 585–589.
SANERSANER-2015-QiuSM #identification #library #morphism #using
Library functions identification in binary code by using graph isomorphism testings (JQ, XS, PM), pp. 261–270.
SANERSANER-2015-SinghGN #data type #memory management
MG++: Memory graphs for analyzing dynamic data structures (VS, RG, IN), pp. 291–300.
SCAMSCAM-2015-LudemannK #control flow
From preprocessor-constrained parse graphs to preprocessor-constrained control flow (DL, RK), pp. 211–220.
CIAACIAA-2015-GusevS #on the
On the Number of Synchronizing Colorings of Digraphs (VVG, MS), pp. 127–139.
ICALPICALP-v1-2015-0001GR #morphism
Counting Homomorphisms to Square-Free Graphs, Modulo 2 (AG, LAG, DR), pp. 642–653.
ICALPICALP-v1-2015-BerkholzG #algebra #morphism #testing
Limitations of Algebraic Approaches to Graph Isomorphism Testing (CB, MG), pp. 155–166.
ICALPICALP-v1-2015-BernsteinS
Fully Dynamic Matching in Bipartite Graphs (AB, CS), pp. 167–179.
ICALPICALP-v1-2015-DoronT #approximate #on the #probability #problem
On the Problem of Approximating the Eigenvalues of Undirected Graphs in Probabilistic Logspace (DD, ATS), pp. 419–431.
ICALPICALP-v1-2015-Erlebach0K #on the
On Temporal Graph Exploration (TE, MH, FK), pp. 444–455.
ICALPICALP-v1-2015-FeldmannFKP #bound
A (1+ε ) ( 1 + ε ) -Embedding of Low Highway Dimension Graphs into Bounded Treewidth Graphs (AEF, WSF, JK, IP), pp. 469–480.
ICALPICALP-v1-2015-FominGKM #bound #morphism #problem
Lower Bounds for the Graph Homomorphism Problem (FVF, AG, ASK, IM), pp. 481–493.
ICALPICALP-v1-2015-GeorgiadisILP
2-Vertex Connectivity in Directed Graphs (LG, GFI, LL, NP), pp. 605–616.
ICALPICALP-v1-2015-HenzingerKN #algorithm #reachability
Improved Algorithms for Decremental Single-Source Reachability on Directed Graphs (MH, SK, DN), pp. 725–736.
ICALPICALP-v1-2015-KannanM0 #complexity #query
Near-Linear Query Complexity for Graph Inference (SK, CM, HZ), pp. 773–784.
ICALPICALP-v1-2015-KawaseKY
Finding a Path in Group-Labeled Graphs with Two Labels Forbidden (YK, YK, YY), pp. 797–809.
ICALPICALP-v2-2015-AchlioptasS #independence #symmetry
Symmetric Graph Properties Have Independent Edges (DA, PS), pp. 467–478.
ICALPICALP-v2-2015-Feldmann #approximate #parametricity #problem
Fixed Parameter Approximations for k-Center Problems in Low Highway Dimension Graphs (AEF), pp. 588–600.
ICALPICALP-v2-2015-FriedrichK #on the #random
On the Diameter of Hyperbolic Random Graphs (TF, AK), pp. 614–625.
ICALPICALP-v2-2015-KawarabayashiK #theorem #towards
Towards the Graph Minor Theorems for Directed Graphs (KiK, SK), pp. 3–10.
LATALATA-2015-CazauxLR #assembly
Construction of a de Bruijn Graph for Assembly from a Truncated Suffix Tree (BC, TL, ER), pp. 109–120.
LATALATA-2015-DabrowskiHP #bound #clique
Bounding Clique-Width via Perfect Graphs (KKD, SH, DP), pp. 676–688.
LATALATA-2015-MakowskyL #matrix #word
Hankel Matrices: From Words to Graphs (JAM, NL), pp. 47–55.
FMFM-2015-ZhuYGZZZ #data flow #model checking #scheduling
Static Optimal Scheduling for Synchronous Data Flow Graphs with Model Checking (XZ, RY, YLG, JZ, WZ, GZ), pp. 551–569.
RTARTA-2015-Kirchner #data analysis
Port Graphs, Rules and Strategies for Dynamic Data Analytics — Extended Abstract (HK), pp. 1–4.
GaMGaM-2015-BakFPR #interpreter #programming language
A Reference Interpreter for the Graph Programming Language GP 2 (CB, GF, DP, CR), pp. 48–64.
GaMGaM-2015-HeussnerPCM #concurrent #object-oriented #towards #verification
Towards Practical Graph-Based Verification for an Object-Oriented Concurrency Model (AH, CMP, CC, BM), pp. 32–47.
GaMGaM-2015-HochMS #programming
Dynamic Programming on Nominal Graphs (NH, UM, MS), pp. 80–96.
GaMGaM-2015-Moreau
Aggregation by Provenance Types: A Technique for Summarising Provenance Graphs (LM), pp. 129–144.
GCMGCM-2015-Flick #correctness #on the #recursion #source code
On Correctness of Graph Programs Relative to Recursively Nested Conditions (NEF), pp. 97–112.
GCMGCM-2015-PeuserH #category theory #composition
Attribution of Graphs by Composition of M, N-adhesive Categories (CP, AH), pp. 66–81.
ICGTICGT-2015-Bruggink0NZ #graph transformation #proving #termination #using
Proving Termination of Graph Transformation Systems Using Weighted Type Graphs over Semirings (HJSB, BK, DN, HZ), pp. 52–68.
ICGTICGT-2015-Horn #clojure #domain-specific language #embedded #pattern matching
Graph Pattern Matching as an Embedded Clojure DSL (TH), pp. 189–204.
ICGTICGT-2015-RadkeABHT #constraints #invariant #ocl #set
Translating Essential OCL Invariants to Nested Graph Constraints Focusing on Set Operations (HR, TA, JSB, AH, GT), pp. 155–170.
CHICHI-2015-CaoLLT #interactive #mining #multi #named #visual notation
g-Miner: Interactive Visual Group Mining on Multivariate Graphs (NC, YRL, LL, HT), pp. 279–288.
HCIHIMI-IKD-2015-SharmaMMTD #modelling
A Team Hiring Solution Based on Graph-Based Modelling of Human Resource Entities (AS, JM, AM, AT, PD), pp. 115–126.
HCIHIMI-IKD-2015-YamashitaS #multi
Edge Bundling in Multi-attributed Graphs (TY, RS), pp. 138–147.
ICEISICEIS-v1-2015-BerroMT #open data #process #statistics
Graph-based ETL Processes for Warehousing Statistical Open Data (AB, IM, OT), pp. 271–278.
ICEISICEIS-v1-2015-FuD #named #scalability #social
ROBE — Knitting a Tight Hub for Shortest Path Discovery in Large Social Graphs (LF, JD), pp. 97–107.
ICEISICEIS-v1-2015-MpindaMSR #database #simulation #using
Graph Database Application using Neo4j — Railroad Planner Simulation (SATM, LGM, MTPS, MXR), pp. 399–403.
CIKMCIKM-2015-AilemRN #clustering #composition #matrix
Co-clustering Document-term Matrices by Direct Maximization of Graph Modularity (MA, FR, MN), pp. 1807–1810.
CIKMCIKM-2015-AnastasiuK #named #nearest neighbour #performance
L2Knng: Fast Exact K-Nearest Neighbor Graph Construction with L2-Norm Pruning (DCA, GK), pp. 791–800.
CIKMCIKM-2015-CaoLX #learning #named
GraRep: Learning Graph Representations with Global Structural Information (SC, WL0, QX), pp. 891–900.
CIKMCIKM-2015-ChenCSS #named #scalability
KSGM: Keynode-driven Scalable Graph Matching (XC, KSC, MLS, PS), pp. 1101–1110.
CIKMCIKM-2015-GarimellaMGS #scalability
Scalable Facility Location for Massive Graphs on Pregel-like Systems (KG, GDFM, AG, MS), pp. 273–282.
CIKMCIKM-2015-HeLJ0 #learning
Learning to Represent Knowledge Graphs with Gaussian Embedding (SH, KL0, GJ, JZ0), pp. 623–632.
CIKMCIKM-2015-KhanGWB #nondeterminism #reliability
Top-k Reliable Edge Colors in Uncertain Graphs (AK, FG, TW, FB), pp. 1851–1854.
CIKMCIKM-2015-PetroniQDKI #clustering #named
HDRF: Stream-Based Partitioning for Power-Law Graphs (FP, LQ, KD, SK, GI), pp. 243–252.
CIKMCIKM-2015-ShangZKK #social #towards
Towards Scale-out Capability on Social Graphs (HS, XZ0, RUK, MK), pp. 253–262.
CIKMCIKM-2015-WangZTCZ #classification
Defragging Subgraph Features for Graph Classification (HW, PZ0, IWT, LC0, CZ), pp. 1687–1690.
CIKMCIKM-2015-YangHQXW #recommendation
A Graph-based Recommendation across Heterogeneous Domains (DY, JH, HQ, YX, WW0), pp. 463–472.
CIKMCIKM-2015-YangZ #classification #framework #online #optimisation
A Min-Max Optimization Framework For Online Graph Classification (PY, PZ), pp. 643–652.
CIKMCIKM-2015-ZhangJRXCY #learning #modelling #query
Learning Entity Types from Query Logs via Graph-Based Modeling (JZ, LJ, AR, SX, YC, PSY), pp. 603–612.
CIKMCIKM-2015-Zhao #clustering #named
gSparsify: Graph Motif Based Sparsification for Graph Clustering (PZ), pp. 373–382.
ECIRECIR-2015-MoranL
Graph Regularised Hashing (SM, VL), pp. 135–146.
ECIRECIR-2015-Peleja #named #sentiment
PopMeter: Linked-Entities in a Sentiment Graph (FP), pp. 785–788.
ECIRECIR-2015-SabetghadamLBR #analysis #reachability
Reachability Analysis of Graph Modelled Collections (SS, ML, RB, AR), pp. 370–381.
ICMLICML-2015-AsterisKDYC
Stay on path: PCA along graph paths (MA, ATK, AGD, HGY, BC), pp. 1728–1736.
ICMLICML-2015-Bai0ZH #kernel
An Aligned Subtree Kernel for Weighted Graphs (LB, LR, ZZ, ERH), pp. 30–39.
ICMLICML-2015-LibbrechtHBN
Entropic Graph-based Posterior Regularization (ML, MMH, JAB, WSN), pp. 1992–2001.
ICMLICML-2015-LiuY #learning #predict
Bipartite Edge Prediction via Transductive Learning over Product Graphs (HL, YY), pp. 1880–1888.
ICMLICML-2015-Pouget-AbadieH #framework
Inferring Graphs from Cascades: A Sparse Recovery Framework (JPA, TH), pp. 977–986.
ICMLICML-2015-YangX15b #clustering #distributed #divide and conquer #framework
A Divide and Conquer Framework for Distributed Graph Clustering (WY, HX), pp. 504–513.
KDDKDD-2015-BeutelAF #behaviour #detection #modelling #predict
Graph-Based User Behavior Modeling: From Prediction to Fraud Detection (AB, LA, CF), pp. 2309–2310.
KDDKDD-2015-ElenbergSBD #distributed #framework #scalability
Beyond Triangles: A Distributed Framework for Estimating 3-profiles of Large Graphs (ERE, KS, MB, AGD), pp. 229–238.
KDDKDD-2015-GleichM #algorithm #learning #using
Using Local Spectral Methods to Robustify Graph-Based Learning Algorithms (DFG, MWM), pp. 359–368.
KDDKDD-2015-HallacLB #clustering #network #optimisation #scalability
Network Lasso: Clustering and Optimization in Large Graphs (DH, JL, SB), pp. 387–396.
KDDKDD-2015-JohanssonD #geometry #learning #similarity #using
Learning with Similarity Functions on Graphs using Matchings of Geometric Embeddings (FDJ, DPD), pp. 467–476.
KDDKDD-2015-KuoWWCYD #multi #segmentation
Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation (CTK, XW, PBW, OTC, JY, ID), pp. 617–626.
KDDKDD-2015-LimK #named
MASCOT: Memory-efficient and Accurate Sampling for Counting Local Triangles in Graph Streams (YL, UK), pp. 685–694.
KDDKDD-2015-LiuWHX #framework #health
Temporal Phenotyping from Longitudinal Electronic Health Records: A Graph Based Framework (CL, FW, JH, HX), pp. 705–714.
KDDKDD-2015-MaoWGS #learning #reduction
Dimensionality Reduction Via Graph Structure Learning (QM, LW, SG, YS), pp. 765–774.
KDDKDD-2015-MottinBG #query
Graph Query Reformulation with Diversity (DM, FB, FG), pp. 825–834.
KDDKDD-2015-ShahKZGF #named #summary
TimeCrunch: Interpretable Dynamic Graph Summarization (NS, DK, TZ, BG, CF), pp. 1055–1064.
KDDKDD-2015-Shun #algorithm #estimation #evaluation #parallel
An Evaluation of Parallel Eccentricity Estimation Algorithms on Undirected Real-World Graphs (JS), pp. 1095–1104.
KDDKDD-2015-SuYSSKVY #feedback
Exploiting Relevance Feedback in Knowledge Graph Search (YS, SY, HS, MS, SK, MV, XY), pp. 1135–1144.
KDDKDD-2015-YanardagV #kernel
Deep Graph Kernels (PY, SVNV), pp. 1365–1374.
KDDKDD-2015-ZhouLB #analysis #clustering
Integrating Vertex-centric Clustering with Edge-centric Clustering for Meta Path Graph Analysis (YZ, LL, DB), pp. 1563–1572.
MLDMMLDM-2015-DhulekarNOY #learning #mining #predict
Seizure Prediction by Graph Mining, Transfer Learning, and Transformation Learning (ND, SN, BO, BY), pp. 32–52.
MLDMMLDM-2015-FerrerSR #approximate #distance #edit distance #heuristic #learning
Learning Heuristics to Reduce the Overestimation of Bipartite Graph Edit Distance Approximation (MF, FS, KR), pp. 17–31.
MLDMMLDM-2015-RiesenFDB #distance #edit distance
Greedy Graph Edit Distance (KR, MF, RD, HB), pp. 3–16.
MLDMMLDM-2015-SejalSTAVIP #query #similarity
Query Click and Text Similarity Graph for Query Suggestions (DS, KGS, VT, DA, KRV, SSI, LMP), pp. 328–341.
SEKESEKE-2015-ZegarraCW #learning #visualisation
Facilitating Peer Learning and Knowledge Sharing in STEM Courses via Pattern Based Graph Visualization (EZ, SKC, JW), pp. 284–289.
SIGIRSIGIR-2015-Al-Dhelaan #multi #named #summary
StarSum: A Simple Star Graph for Multi-document Summarization (MAD), pp. 715–718.
SIGIRSIGIR-2015-GuoL #automation #generative #music #recommendation
Automatic Feature Generation on Heterogeneous Graph for Music Recommendation (CG, XL), pp. 807–810.
SIGIRSIGIR-2015-YuM #quality #similarity
High Quality Graph-Based Similarity Search (WY, JAM), pp. 83–92.
PEPMPEPM-2015-BahrA #traversal
Generalising Tree Traversals to DAGs: Exploiting Sharing without the Pain (PB, EA), pp. 27–38.
PLDIPLDI-2015-JohnsonWMC #dependence #security
Exploring and enforcing security guarantees via program dependence graphs (AJ, LW, SM, SC), pp. 291–302.
PLDIPLDI-2015-LalQ #source code
DAG inlining: a decision procedure for reachability-modulo-theories in hierarchical programs (AL, SQ), pp. 280–290.
PLDIPLDI-2015-PrountzosMP #automation #parallel #source code
Synthesizing parallel graph programs via automated planning (DP, RM, KP), pp. 533–544.
POPLPOPL-2015-BonchiSZ #abstraction
Full Abstraction for Signal Flow Graphs (FB, PS, FZ), pp. 515–526.
ASEASE-2015-YangZWWYR #android
Static Window Transition Graphs for Android (T) (SY, HZ, HW, YW, DY, AR), pp. 658–668.
ICSEICSE-v1-2015-NguyenN #statistics
Graph-Based Statistical Language Model for Code (ATN, TNN), pp. 858–868.
SACSAC-2015-CamaraHJJ #modelling #persuasion #recommendation #social #using
Using graph-based models in a persuasive social recommendation system (JPC, SH, JJ, VJ), pp. 189–194.
SACSAC-2015-FerreiraPC #matrix
Exploring graph topology via matrix factorization to improve wikification (RF, MdGCP, MC), pp. 1099–1104.
SACSAC-2015-GimenesGRG #analysis #multimodal #repository
Multimodal graph-based analysis over the DBLP repository: critical discoveries and hypotheses (GPG, HG, JFRJ, MG), pp. 1129–1135.
SACSAC-2015-GuedesBOX #clustering #multi
Exploring multiple clusterings in attributed graphs (GPG, EB, ESO, GX), pp. 915–918.
SACSAC-2015-MiyashitaITK #distributed #named #representation
Catalogue: graph representation of file relations for a globally distributed environment (YM, HI, FT, KK), pp. 806–809.
SACSAC-2015-SioutisSC #composition #on the #reasoning
On the use and effect of graph decomposition in qualitative spatial and temporal reasoning (MS, YS, JFC), pp. 1874–1879.
ASPLOSASPLOS-2015-HassaanNP #dependence
Kinetic Dependence Graphs (MAH, DDN, KP), pp. 457–471.
CASECASE-2015-HeLG #optimisation
Cycle time optimization of deterministic timed weighted marked graphs (ZH, ZL, AG), pp. 274–279.
CASECASE-2015-KouiderHOO #approach #integer #linear #scheduling #source code
Mixed integer linear programs and tabu search approach to solve mixed graph coloring for unit-time job shop scheduling (AK, HAH, SO, AO), pp. 1177–1181.
CGOCGO-2015-LeissaKH #higher-order #representation
A graph-based higher-order intermediate representation (RL, MK, SH), pp. 202–212.
DACDAC-2015-HanF #analysis #approach #cpu #gpu #scalability
Transient-simulation guided graph sparsification approach to scalable harmonic balance (HB) analysis of post-layout RF circuits leveraging heterogeneous CPU-GPU computing systems (LH, ZF), p. 6.
DACDAC-2015-SripadaP #approach
A timing graph based approach to mode merging (SS, MP), p. 6.
DATEDATE-2015-Baruah #scheduling
The federated scheduling of constrained-deadline sporadic DAG task systems (SB), pp. 1323–1328.
HPDCHPDC-2015-YangC #behaviour #benchmark #comprehension #metric #robust
Understanding Graph Computation Behavior to Enable Robust Benchmarking (FY, AAC), pp. 173–178.
HPDCHPDC-2015-ZhouLLPZ #abstraction #parallel #performance
Fast Iterative Graph Computation with Resource Aware Graph Parallel Abstractions (YZ, LL, KL, CP, QZ), pp. 179–190.
PDPPDP-2015-AliAP #data flow #parametricity #realtime
Generalized Extraction of Real-Time Parameters for Homogeneous Synchronous Dataflow Graphs (HIA, BA, LMP), pp. 701–710.
PPoPPPPoPP-2015-HarshvardhanAR #algorithm #approach #communication #parallel
A hierarchical approach to reducing communication in parallel graph algorithms (H, NMA, LR), pp. 285–286.
PPoPPPPoPP-2015-SeoKK #named #scalability #streaming
GStream: a graph streaming processing method for large-scale graphs on GPUs (HS, JK, MSK), pp. 253–254.
PPoPPPPoPP-2015-ShiLDHJLWLZ #gpu #hybrid #optimisation
Optimization of asynchronous graph processing on GPU with hybrid coloring model (XS, JL, SD, BH, HJ, LL, ZW, XL, JZ), pp. 271–272.
PPoPPPPoPP-2015-WangDPWRO #gpu #library #named
Gunrock: a high-performance graph processing library on the GPU (YW, AAD, YP, YW, AR, JDO), pp. 265–266.
SOSPSOSP-2015-0002BMZ #named
Chaos: scale-out graph processing from secondary storage (AR, LB, JM, WZ), pp. 410–424.
SOSPSOSP-2015-TeixeiraFSSZA #distributed #mining #named
Arabesque: a system for distributed graph mining (CHCT, AJF, MS, GS, MJZ, AA), pp. 425–440.
STOCSTOC-2015-AlstrupKTZ
Adjacency Labeling Schemes and Induced-Universal Graphs (SA, HK, MT, UZ), pp. 625–634.
STOCSTOC-2015-AlwenS #complexity #parallel
High Parallel Complexity Graphs and Memory-Hard Functions (JA, VS), pp. 595–603.
STOCSTOC-2015-BansalGG #independence #on the #set
On the Lovász Theta function for Independent Sets in Sparse Graphs (NB, AG, GG), pp. 193–200.
STOCSTOC-2015-Bresler #learning #modelling
Efficiently Learning Ising Models on Arbitrary Graphs (GB), pp. 771–782.
STOCSTOC-2015-ChawlaMSY #algorithm #clustering
Near Optimal LP Rounding Algorithm for CorrelationClustering on Complete and Complete k-partite Graphs (SC, KM, TS, GY), pp. 219–228.
STOCSTOC-2015-CzumajPS #clustering #testing
Testing Cluster Structure of Graphs (AC, PP, CS), pp. 723–732.
STOCSTOC-2015-HalldorssonT #how #question
How Well Can Graphs Represent Wireless Interference? (MMH, TT), pp. 635–644.
STOCSTOC-2015-KawarabayashiS #approximate
Beyond the Euler Characteristic: Approximating the Genus of General Graphs (KiK, AS), pp. 675–682.
STOCSTOC-2015-KawarabayashiT
Deterministic Global Minimum Cut of a Simple Graph in Near-Linear Time (KiK, MT), pp. 665–674.
STOCSTOC-2015-Lee
Hardness of Graph Pricing Through Generalized Max-Dicut (EL), pp. 391–399.
CAVCAV-2015-ChatterjeeIP #algorithm #constant #performance #verification
Faster Algorithms for Quantitative Verification in Constant Treewidth Graphs (KC, RIJ, AP), pp. 140–157.
CAVCAV-2015-ErezN #automation #bound #smt #using
Finding Bounded Path in Graph Using SMT for Automatic Clock Routing (AE, AN), pp. 20–36.
ICTSSICTSS-2015-HalleCG #constraints #generative #testing
Graph Methods for Generating Test Cases with Universal and Existential Constraints (SH, ELC, SG), pp. 55–70.
LICSLICS-2015-FigueiraL #logic #performance #query
Path Logics for Querying Graphs: Combining Expressiveness and Efficiency (DF, LL), pp. 329–340.
LICSLICS-2015-Reiter #automaton #distributed
Distributed Graph Automata (FR), pp. 192–201.
QoSAQoSA-2014-JohnsenLPH #dependence #modelling #slicing #verification
Regression verification of AADL models through slicing of system dependence graphs (AJ, KL, PP, KH), pp. 103–112.
DocEngDocEng-2014-LimaBFFLSR
Transforming graph-based sentence representations to alleviate overfitting in relation extraction (RJL, JB, RF, FF, RDL, SJS, MR), pp. 53–62.
JCDLJCDL-2014-ZhuCBW #named #visualisation
CKGHV: a comprehensive knowledge graph for history visualization (YZ, XC, YB, JW), pp. 437–438.
PODSPODS-2014-Cohen #analysis #sketching
All-distances sketches, revisited: HIP estimators for massive graphs analysis (EC), pp. 88–99.
SIGMODSIGMOD-2014-AroraSB #mining #statistics
Mining statistically significant connected subgraphs in vertex labeled graphs (AA, MS, AB), pp. 1003–1014.
SIGMODSIGMOD-2014-CuiXWW #community #scalability
Local search of communities in large graphs (WC, YX, HW, WW), pp. 991–1002.
SIGMODSIGMOD-2014-Dev14a #community #detection #precise #privacy #social
Privacy preserving social graphs for high precision community detection (HD), pp. 1615–1616.
SIGMODSIGMOD-2014-FanWW #bound #query
Querying big graphs within bounded resources (WF, XW, YW), pp. 301–312.
SIGMODSIGMOD-2014-HuangCQTY #community #query #scalability
Querying k-truss community in large and dynamic graphs (XH, HC, LQ, WT, JXY), pp. 1311–1322.
SIGMODSIGMOD-2014-KimHLPY #framework #named #parallel #scalability
OPT: a new framework for overlapped and parallel triangulation in large-scale graphs (JK, WSH, SL, KP, HY), pp. 637–648.
SIGMODSIGMOD-2014-MondalD #named #query #scalability
EAGr: supporting continuous ego-centric aggregate queries over large dynamic graphs (JM, AD), pp. 1335–1346.
SIGMODSIGMOD-2014-PapailiouTKKK #data transformation #performance #rdf
H2RDF+: an efficient data management system for big RDF graphs (NP, DT, IK, PK, NK), pp. 909–912.
SIGMODSIGMOD-2014-ParchasGPB #nondeterminism
The pursuit of a good possible world: extracting representative instances of uncertain graphs (PP, FG, DP, FB), pp. 967–978.
SIGMODSIGMOD-2014-QinYCCZL #pipes and filters #scalability
Scalable big graph processing in MapReduce (LQ, JXY, LC, HC, CZ, XL), pp. 827–838.
SIGMODSIGMOD-2014-RanuHS #database #query
Answering top-k representative queries on graph databases (SR, MXH, AKS), pp. 1163–1174.
SIGMODSIGMOD-2014-SatishSPSPHSYD #dataset #framework #navigation #using
Navigating the maze of graph analytics frameworks using massive graph datasets (NS, NS, MMAP, JS, JP, MAH, SS, ZY, PD), pp. 979–990.
SIGMODSIGMOD-2014-ShaoCCMYX #parallel #scalability
Parallel subgraph listing in a large-scale graph (YS, BC, LC, LM, JY, NX), pp. 625–636.
SIGMODSIGMOD-2014-SricharanD
Localizing anomalous changes in time-evolving graphs (KS, KD), pp. 1347–1358.
SIGMODSIGMOD-2014-WuJZ #nearest neighbour #performance #query #random #scalability
Fast and unified local search for random walk based k-nearest-neighbor query in large graphs (YW, RJ, XZ), pp. 1139–1150.
SIGMODSIGMOD-2014-YangXWWSWY #named #query
SLQ: a user-friendly graph querying system (SY, YX, YW, TW, HS, JW, XY), pp. 893–896.
SIGMODSIGMOD-2014-ZhuGCL #analysis #clustering #sentiment #social #social media
Tripartite graph clustering for dynamic sentiment analysis on social media (LZ, AG, JC, KL), pp. 1531–1542.
SIGMODSIGMOD-2014-ZhuLWX #approach #order #query #reachability #scalability
Reachability queries on large dynamic graphs: a total order approach (ADZ, WL, SW, XX), pp. 1323–1334.
SIGMODSIGMOD-2014-ZouHWYHZ #approach #data-driven #natural language #rdf
Natural language question answering over RDF: a graph data driven approach (LZ, RH, HW, JXY, WH, DZ), pp. 313–324.
VLDBVLDB-2014-ArenasDFKS #approach
A Principled Approach to Bridging the Gap between Graph Data and their Schemas (MA, GID, AF, AK, KS), pp. 601–612.
VLDBVLDB-2014-ElseidyASK #mining #named #scalability
GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph (ME, EA, SS, PK), pp. 517–528.
VLDBVLDB-2014-FanWWD #distributed #simulation
Distributed Graph Simulation: Impossibility and Possibility (WF, XW, YW, DD), pp. 1083–1094.
VLDBVLDB-2014-GuptaSGGZLL #detection #online #realtime #recommendation #scalability #twitter
Real-Time Twitter Recommendation: Online Motif Detection in Large Dynamic Graphs (PG, VS, AG, SG, VZ, QL, JL), pp. 1379–1380.
VLDBVLDB-2014-HanDAOWJ #comparison
An Experimental Comparison of Pregel-like Graph Processing Systems (MH, KD, KA, MTÖ, XW, TJ), pp. 1047–1058.
VLDBVLDB-2014-JindalR0MDS #exclamation #named #relational
VERTEXICA: Your Relational Friend for Graph Analytics! (AJ, PR, EW, SM, AD, MS), pp. 1669–1672.
VLDBVLDB-2014-MaeharaAIK #personalisation #rank
Computing Personalized PageRank Quickly by Exploiting Graph Structures (TM, TA, YI, KiK), pp. 1023–1034.
VLDBVLDB-2014-PetermannJMR #integration
Graph-based Data Integration and Business Intelligence with BIIIG (AP, MJ, RM, ER), pp. 1577–1580.
VLDBVLDB-2014-QuamarDL #named #scalability
NScale: Neighborhood-centric Analytics on Large Graphs (AQ, AD, JL), pp. 1673–1676.
VLDBVLDB-2014-SalihogluW #algorithm #optimisation
Optimizing Graph Algorithms on Pregel-like Systems (SS, JW), pp. 577–588.
VLDBVLDB-2014-ShangY #approximate
Auto-Approximation of Graph Computing (ZS, JXY), pp. 1833–1844.
VLDBVLDB-2014-SimmenSDHLMSTX #big data #scalability
Large-Scale Graph Analytics in Aster 6: Bringing Context to Big Data Discovery (DES, KS, JD, YH, SL, AM, VS, MT, YX), pp. 1405–1416.
VLDBVLDB-2014-WuCHKLX #problem
Path Problems in Temporal Graphs (HW, JC, SH, YK, YL, YX), pp. 721–732.
VLDBVLDB-2014-XuCC #clustering #named
LogGP: A Log-based Dynamic Graph Partitioning Method (NX, LC, BC), pp. 1917–1928.
VLDBVLDB-2014-YanCLN #distributed #framework #named
Blogel: A Block-Centric Framework for Distributed Computation on Real-World Graphs (DY, JC, YL, WN), pp. 1981–1992.
VLDBVLDB-2014-YanCXLNB #algorithm #performance #problem
Pregel Algorithms for Graph Connectivity Problems with Performance Guarantees (DY, JC, KX, YL, WN, YB), pp. 1821–1832.
VLDBVLDB-2014-YangGYL #constraints
Finding the Cost-Optimal Path with Time Constraint over Time-Dependent Graphs (YY, HG, JXY, JL), pp. 673–684.
VLDBVLDB-2014-YangWSY #query
Schemaless and Structureless Graph Querying (SY, YW, HS, XY), pp. 565–576.
VLDBVLDB-2015-BuBJCC14 #data flow #named
Pregelix: Big(ger) Graph Analytics on a Dataflow Engine (YB, VRB, JJ, MJC, TC), pp. 161–172.
VLDBVLDB-2015-LuCYW14 #distributed #evaluation #scalability
Large-Scale Distributed Graph Computing Systems: An Experimental Evaluation (YL, JC, DY, HW), pp. 281–292.
VLDBVLDB-2015-ShenCJLOT14 #distributed #performance
Fast Failure Recovery in Distributed Graph Processing Systems (YS, GC, HVJ, WL, BCO, BMT), pp. 437–448.
VLDBVLDB-2015-SongGCW14 #pattern matching
Event Pattern Matching over Graph Streams (CS, TG, CXC, JW), pp. 413–424.
VLDBVLDB-2015-ThenKCHPK0V14 #multi #performance #traversal
The More the Merrier: Efficient Multi-Source Graph Traversal (MT, MK, FC, TAHV, KP, AK, TN, HTV), pp. 449–460.
VLDBVLDB-2015-ZhouGSY14 #distributed #named #online #scalability #using
MOCgraph: Scalable Distributed Graph Processing Using Message Online Computing (CZ, JG, BS, JXY), pp. 377–388.
VLDBVLDB-2015-ZhuYQ14 #online
Leveraging Graph Dimensions in Online Graph Search (YZ, JXY, LQ), pp. 85–96.
CSEETCSEET-2014-Steppe #analysis #dependence #design #education #using
Teaching analysis of software designs using dependency graphs (KS), pp. 65–73.
ICSMEICSME-2014-BhattacharyaNF #approach #developer
Determining Developers’ Expertise and Role: A Graph Hierarchy-Based Approach (PB, IN, MF), pp. 11–20.
SCAMSCAM-2014-Abi-AntounCVG #abstract interpretation #question #using
Are Object Graphs Extracted Using Abstract Interpretation Significantly Different from the Code? (MAA, SC, RV, AG), pp. 245–254.
DLTDLT-J-2013-TanV14 #query #regular expression
Regular Expressions for Querying Data graphs (TT, DV), pp. 971–986.
DLTDLT-2014-BerdinskyK #automation #on the #transitive
On Automatic Transitive Graphs (DB, BK), pp. 1–12.
DLTDLT-2014-Sinya #automaton #finite
Graph Spectral Properties of Deterministic Finite Automata — (RS), pp. 76–83.
ICALPICALP-v1-2014-AngeliniLBFPR
Morphing Planar Graph Drawings Optimally (PA, GDL, GDB, FF, MP, VR), pp. 126–137.
ICALPICALP-v1-2014-BaswanaK #algorithm #incremental #maintenance
Incremental Algorithm for Maintaining DFS Tree for Undirected Graphs (SB, SK), pp. 138–149.
ICALPICALP-v1-2014-BevernBBCFNW
Star Partitions of Perfect Graphs (RvB, RB, LB, JC, VF, RN, GJW), pp. 174–185.
ICALPICALP-v1-2014-Biedl #on the
On Area-Optimal Planar Graph Drawings (TCB), pp. 198–210.
ICALPICALP-v1-2014-DapicMM
QCSP on Semicomplete Digraphs (PD, PM, BM), pp. 847–858.
ICALPICALP-v1-2014-FialaKKN #algorithm #aspect-oriented
Algorithmic Aspects of Regular Graph Covers with Applications to Planar Graphs (JF, PK, JK, RN), pp. 489–501.
ICALPICALP-v1-2014-KrawczykW #game studies #online
Coloring Relatives of Interval Overlap Graphs via On-line Games (TK, BW), pp. 738–750.
ICALPICALP-v1-2014-Lampis #approximate #using
Parameterized Approximation Schemes Using Graph Widths (ML), pp. 775–786.
ICALPICALP-v1-2014-MakarychevM #clustering
Nonuniform Graph Partitioning with Unrelated Weights (KM, YM), pp. 812–822.
ICALPICALP-v1-2014-ReingoldRW #data type #pseudo
Pseudorandom Graphs in Data Structures (OR, RDR, UW), pp. 943–954.
ICALPICALP-v1-2014-TulsianiWZ #game studies #parallel #rank
Optimal Strong Parallel Repetition for Projection Games on Low Threshold Rank Graphs (MT, JW, YZ), pp. 1003–1014.
ICALPICALP-v1-2014-Wulff-Nilsen #approximate #distance #performance
Faster Separators for Shallow Minor-Free Graphs via Dynamic Approximate Distance Oracles (CWN), pp. 1063–1074.
ICALPICALP-v1-2014-Yin #random
Spatial Mixing of Coloring Random Graphs (YY), pp. 1075–1086.
ICALPICALP-v2-2014-AdjiashviliR #bound
Labeling Schemes for Bounded Degree Graphs (DA, NR), pp. 375–386.
ICALPICALP-v2-2014-GiakkoupisSS #random
Randomized Rumor Spreading in Dynamic Graphs (GG, TS, AS), pp. 495–507.
ICALPICALP-v2-2014-KopelowitzKPS #bound #worst-case
Orienting Fully Dynamic Graphs with Worst-Case Time Bounds (TK, RK, EP, SS), pp. 532–543.
LATALATA-2014-BeerenwinkelBBDP
Covering Pairs in Directed Acyclic Graphs (NB, SB, PB, RD, YP), pp. 126–137.
LATALATA-2014-BestD #bound #petri net
Characterisation of the State Spaces of Live and Bounded Marked Graph Petri Nets (EB, RRD), pp. 161–172.
LATALATA-2014-DasST #encoding #morphism
Succinct Encodings of Graph Isomorphism (BD, PS, JT), pp. 285–296.
FMFM-2014-RinastSG #performance #reduction
A Graph-Based Transformation Reduction to Reach UPPAAL States Faster (JR, SS, DG), pp. 547–562.
FLOPSFLOPS-2014-Bahr #compilation #correctness #proving #using
Proving Correctness of Compilers Using Structured Graphs (PB), pp. 221–237.
CHI-PLAYCHI-PLAY-2014-PommerFGSLPTD #game studies
The trial of galileo: a game of motion graphs (IP, MNF, AG, BS, JL, KP, DT, BD), pp. 363–366.
CoGCIG-2014-GrafP #monte carlo
Common fate graph patterns in Monte Carlo Tree Search for computer go (TG, MP), pp. 1–8.
CoGCIG-2014-KimYK #geometry #monte carlo #representation #using
Solving Geometry Friends using Monte-Carlo Tree Search with directed graph representation (HTK, DMY, KJK), pp. 1–2.
GT-VMTGT-VMT-2014-WangBL #alloy #model transformation #using #verification
Verification of Graph-based Model Transformations Using Alloy (XW, FB, YL).
ICGTICGT-2014-ArendtHRT #constraints #invariant #ocl
From Core OCL Invariants to Nested Graph Constraints (TA, AH, HR, GT), pp. 97–112.
ICGTICGT-2014-DeckwerthV #constraints #generative
Attribute Handling for Generating Preconditions from Graph Constraints (FD, GV), pp. 81–96.
ICGTICGT-2014-JansenN #generative #pointer #source code #summary
Generating Abstract Graph-Based Procedure Summaries for Pointer Programs (CJ, TN), pp. 49–64.
ICGTICGT-2014-LambersO #reasoning
Tableau-Based Reasoning for Graph Properties (LL, FO), pp. 17–32.
ICGTICGT-2014-PoskittP #higher-order #monad #source code #verification
Verifying Monadic Second-Order Properties of Graph Programs (CMP, DP), pp. 33–48.
ICGTICGT-2014-SelimLCDO #model transformation #specification #verification
Specification and Verification of Graph-Based Model Transformation Properties (GMKS, LL, JRC, JD, BJO), pp. 113–129.
HCIDUXU-DI-2014-AcarturkAH #comprehension
Developing a Verbal Assistance System for Line Graph Comprehension (CA, ÖA, CH), pp. 373–382.
HCIDUXU-ELAS-2014-FloraB #behaviour #energy #feedback
Energy Graph Feedback: Attention, Cognition and Behavior Intentions (JAF, BB), pp. 520–529.
VISSOFTVISSOFT-2014-BergelMDG #dependence #domain-specific language #visualisation
A Domain-Specific Language for Visualizing Software Dependencies as a Graph (AB, SM, SD, TG), pp. 45–49.
VISSOFTVISSOFT-2014-MartinezZMBKT #constraints #paradigm #product line #visualisation
Feature Relations Graphs: A Visualisation Paradigm for Feature Constraints in Software Product Lines (JM, TZ, RM, TFB, JK, YLT), pp. 50–59.
ICEISICEIS-v1-2014-PinheiroCML #algorithm
An Evolutionary Algorithm for Graph Planarisation by Vertex Deletion (RLP, AAC, CFXdM, DLS), pp. 464–471.
CIKMCIKM-2014-AgrawalGKK #concept #similarity #using
Similarity Search using Concept Graphs (RA, SG, AK, KK), pp. 719–728.
CIKMCIKM-2014-LiakosPS
Pushing the Envelope in Graph Compression (PL, KP, MS), pp. 1549–1558.
CIKMCIKM-2014-LiuTHLM #distributed #summary
Distributed Graph Summarization (XL, YT, QH, WCL, JM), pp. 799–808.
CIKMCIKM-2014-LiuYGS #feedback #pseudo #ranking #recommendation
Meta-Path-Based Ranking with Pseudo Relevance Feedback on Heterogeneous Graph for Citation Recommendation (XL, YY, CG, YS), pp. 121–130.
CIKMCIKM-2014-MassS #information management #keyword
Knowledge Management for Keyword Search over Data Graphs (YM, YS), pp. 2051–2053.
CIKMCIKM-2014-SpirinHDKB #analysis #facebook #network #online #people #query #scalability #social
People Search within an Online Social Network: Large Scale Analysis of Facebook Graph Search Query Logs (NVS, JH, MD, KGK, MB), pp. 1009–1018.
CIKMCIKM-2014-TongZC0 #nondeterminism #performance #probability #scalability
Efficient Probabilistic Supergraph Search Over Large Uncertain Graphs (YT, XZ, CCC, LC), pp. 809–818.
CIKMCIKM-2014-YuanCS #recommendation
Graph-based Point-of-interest Recommendation with Geographical and Temporal Influences (QY, GC, AS), pp. 659–668.
CIKMCIKM-2014-YuanW0 #nondeterminism #query #scalability
Pattern Match Query in a Large Uncertain Graph (YY, GW, LC), pp. 519–528.
CIKMCIKM-2014-ZhangLLW #multi #named
PatentDom: Analyzing Patent Relationships on Multi-View Patent Graphs (LZ, LL, TL, DW), pp. 1369–1378.
CIKMCIKM-2014-ZhangP #nondeterminism #scalability
Scalable Vaccine Distribution in Large Graphs given Uncertain Data (YZ, BAP), pp. 1719–1728.
CIKMCIKM-2014-ZhengZLHZ #performance #scalability
Efficient Subgraph Skyline Search Over Large Graphs (WZ, LZ, XL, LH, DZ), pp. 1529–1538.
ECIRECIR-2014-GhamdiG #retrieval #video
Video Clip Retrieval by Graph Matching (MAG, YG), pp. 412–417.
ICMLICML-c1-2014-ChanA #consistency #modelling
A Consistent Histogram Estimator for Exchangeable Graph Models (SHC, EA), pp. 208–216.
ICMLICML-c1-2014-TandonR #learning
Learning Graphs with a Few Hubs (RT, PDR), pp. 602–610.
ICMLICML-c2-2014-BratieresQNG #grid #predict #process #scalability
Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications (SB, NQ, SN, ZG), pp. 334–342.
ICMLICML-c2-2014-ChenLX #clustering #nondeterminism
Weighted Graph Clustering with Non-Uniform Uncertainties (YC, SHL, HX), pp. 1566–1574.
ICMLICML-c2-2014-FangCL #learning
Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically (YF, KCCC, HWL), pp. 406–414.
ICMLICML-c2-2014-JohanssonJDB #geometry #kernel #using
Global graph kernels using geometric embeddings (FJ, VJ, DPD, CB), pp. 694–702.
ICMLICML-c2-2014-KurrasLB #geometry
The f-Adjusted Graph Laplacian: a Diagonal Modification with a Geometric Interpretation (SK, UvL, GB), pp. 1530–1538.
ICMLICML-c2-2014-RavanbakhshSFG #problem
Min-Max Problems on Factor Graphs (S(R, CS, BJF, RG), pp. 1035–1043.
ICMLICML-c2-2014-ValkoMKK
Spectral Bandits for Smooth Graph Functions (MV, RM, BK, TK), pp. 46–54.
ICPRICPR-2014-AzizWH #kernel #using
Graph Characterization Using Wave Kernel Trace (FA, RCW, ERH), pp. 3822–3827.
ICPRICPR-2014-BaiBH #kernel
An Attributed Graph Kernel from the Jensen-Shannon Divergence (LB, HB, ERH), pp. 88–93.
ICPRICPR-2014-BaiHRE #complexity
Directed Depth-Based Complexity Traces of Hypergraphs from Directed Line Graphs (LB, ERH, PR, FE), pp. 3874–3879.
ICPRICPR-2014-BertonL #learning
Graph Construction Based on Labeled Instances for Semi-supervised Learning (LB, AdAL), pp. 2477–2482.
ICPRICPR-2014-BuiNK #music #using
Staff Line Removal Using Line Adjacency Graph and Staff Line Skeleton for Camera-Based Printed Music Scores (HNB, ISN, SHK), pp. 2787–2789.
ICPRICPR-2014-ChandrasekharTMLLL #clustering #incremental #performance #retrieval #streaming #video
Incremental Graph Clustering for Efficient Retrieval from Streaming Egocentric Video Data (VC, CT, WM, LL, XL, JHL), pp. 2631–2636.
ICPRICPR-2014-DiotFJMM #clustering
Unsupervised Tracking from Clustered Graph Patterns (FD, ÉF, BJ, EM, OM), pp. 3678–3683.
ICPRICPR-2014-DornaikaBSR #classification #encoding #locality
Locality Constrained Encoding Graph Construction and Application to Outdoor Object Classification (FD, AB, HS, YR), pp. 2483–2488.
ICPRICPR-2014-EscolanoH
The Mutual Information between Graphs (FE, ERH), pp. 94–99.
ICPRICPR-2014-FuGYGY #detection
Graph Construction for Salient Object Detection in Videos (KF, IYHG, YY, CG, JY), pp. 2371–2376.
ICPRICPR-2014-GauzereBV #encoding #kernel
Graph Kernel Encoding Substituents’ Relative Positioning (BG, LB, DV), pp. 637–642.
ICPRICPR-2014-GrenierBV #kernel
A Graph Kernel Incorporating Molecule’s Stereisomerism Information (PAG, LB, DV), pp. 631–636.
ICPRICPR-2014-GuoDM #recognition
Graph-Based Kinship Recognition (YG, HD, LvdM), pp. 4287–4292.
ICPRICPR-2014-HachaniZP
Kinematic Reeb Graph Extraction Based on Heat Diffusion (MH, AOZ, WP), pp. 3981–3986.
ICPRICPR-2014-Jain
Margin Perceptrons for Graphs (BJJ), pp. 3851–3856.
ICPRICPR-2014-KuangLJL #3d
Graph Contexts for Retrieving Deformable Non-rigid 3D Shapes (ZK, ZL, XJ, YL), pp. 2820–2825.
ICPRICPR-2014-LinnerS #alias #anti #distance #implementation
A Graph-Based Implementation of the Anti-aliased Euclidean Distance Transform (EL, RS), pp. 1025–1030.
ICPRICPR-2014-LiuLFQGT #geometry #retrieval
Plane Geometry Figure Retrieval Based on Bilayer Geometric Attributed Graph Matching (LL, XL, SF, JQ, LG, ZT), pp. 309–314.
ICPRICPR-2014-LiuZH #energy #optimisation
Improved Optimization Based on Graph Cuts for Discrete Energy Minimization (KL, JZ, KH), pp. 2424–2429.
ICPRICPR-2014-ManfrediGC #energy #image #learning #segmentation
Learning Graph Cut Energy Functions for Image Segmentation (MM, CG, RC), pp. 960–965.
ICPRICPR-2014-MutimbuR #image
Factor Graphs for Image Processing (LDM, ARK), pp. 1443–1448.
ICPRICPR-2014-NocetiO #classification #kernel #process
A Spectral Graph Kernel and Its Application to Collective Activities Classification (NN, FO), pp. 3892–3897.
ICPRICPR-2014-NourbakhshBP #approach #matrix
A Matrix Factorization Approach to Graph Compression (FN, SRB, MP), pp. 76–81.
ICPRICPR-2014-OskarssonAT #multi #scalability
Prime Rigid Graphs and Multidimensional Scaling with Missing Data (MO, , AT), pp. 750–755.
ICPRICPR-2014-PandaKC #random #scalability #summary #using #video
Scalable Video Summarization Using Skeleton Graph and Random Walk (RP, SKK, ASC), pp. 3481–3486.
ICPRICPR-2014-PhamKC #image #learning
Semi-supervised Learning on Bi-relational Graph for Image Annotation (HDP, KHK, SC), pp. 2465–2470.
ICPRICPR-2014-RiesenBF #approximate #distance #edit distance #metric
Improving Graph Edit Distance Approximation by Centrality Measures (KR, HB, AF), pp. 3910–3914.
ICPRICPR-2014-RozzaMP #kernel #learning #novel
A Novel Graph-Based Fisher Kernel Method for Semi-supervised Learning (AR, MM, AP), pp. 3786–3791.
ICPRICPR-2014-SilvaTT #approach #named
BoG: A New Approach for Graph Matching (FBS, ST, RdST), pp. 82–87.
ICPRICPR-2014-WangEGLLF #approach #distance #documentation #edit distance #word
A Coarse-to-Fine Word Spotting Approach for Historical Handwritten Documents Based on Graph Embedding and Graph Edit Distance (PW, VE, CG, CL, JL, AF), pp. 3074–3079.
ICPRICPR-2014-Wilson #modelling #network
Graph Signatures for Evaluating Network Models (RCW), pp. 100–105.
ICPRICPR-2014-YeWH #analysis #component
Graph Characterization from Entropy Component Analysis (CY, RCW, ERH), pp. 3845–3850.
KDDKDD-2014-AhmedDNK #framework
Graph sample and hold: a framework for big-graph analytics (NKA, NGD, JN, RRK), pp. 1446–1455.
KDDKDD-2014-BonchiGKV #composition #nondeterminism
Core decomposition of uncertain graphs (FB, FG, AK, YV), pp. 1316–1325.
KDDKDD-2014-BordesG #mining #tutorial
Constructing and mining web-scale knowledge graphs: KDD 2014 tutorial (AB, EG), p. 1967.
KDDKDD-2014-BourseLV
Balanced graph edge partition (FB, ML, MV), pp. 1456–1465.
KDDKDD-2014-ChenN #detection #parametricity #social #social media #statistics
Non-parametric scan statistics for event detection and forecasting in heterogeneous social media graphs (FC, DBN), pp. 1166–1175.
KDDKDD-2014-DuanSLL #community #correlation #detection
Community detection in graphs through correlation (LD, WNS, YL, HL), pp. 1376–1385.
KDDKDD-2014-GaddeAO #learning #using
Active semi-supervised learning using sampling theory for graph signals (AG, AA, AO), pp. 492–501.
KDDKDD-2014-JiangCBFY #behaviour #named #scalability
CatchSync: catching synchronized behavior in large directed graphs (MJ, PC, AB, CF, SY), pp. 941–950.
KDDKDD-2014-LofgrenBGC #estimation #named #personalisation #rank #scalability
FAST-PPR: scaling personalized pagerank estimation for large graphs (PL, SB, AG, SC), pp. 1436–1445.
KDDKDD-2014-LuM #difference #estimation #exponential #privacy #random
Exponential random graph estimation under differential privacy (WL, GM), pp. 921–930.
KDDKDD-2014-PerozziASM #clustering #detection #scalability
Focused clustering and outlier detection in large attributed graphs (BP, LA, PIS, EM), pp. 1346–1355.
KDDKDD-2014-TamersoyRC #detection #mining #scalability
Guilt by association: large scale malware detection by mining file-relation graphs (AT, KAR, DHC), pp. 1524–1533.
KDDKDD-2014-ZhouT #multi
Multi-task copula by sparse graph regression (TZ, DT), pp. 771–780.
KDIRKDIR-2014-CastelltortL #analysis
NoSQL Graph-based OLAP Analysis (AC, AL), pp. 217–224.
KDIRKDIR-2014-MohammadiMBRA #classification #parametricity
A Noise Resilient and Non-parametric Graph-based Classifier (MM, SAM, EB, BR, AA), pp. 170–175.
KEODKEOD-2014-SurynekS #big data #challenge #information management #logic #perspective #reasoning
Theoretical Challenges in Knowledge Discovery in Big Data — A Logic Reasoning and a Graph Theoretical Point of View (PS, PS), pp. 327–332.
KRKR-2014-FiondaGP #web
Knowledge Maps of Web Graphs (VF, CG, GP).
KRKR-2014-Schuller #formal method
Tackling Winograd Schemas by Formalizing Relevance Theory in Knowledge Graphs (PS).
MLDMMLDM-2014-SchraagenK #consistency #using
Record Linkage Using Graph Consistency (MS, WAK), pp. 471–483.
RecSysRecSys-2014-PetroniQ #clustering #distributed #matrix #named #probability
GASGD: stochastic gradient descent for distributed asynchronous matrix completion via graph partitioning (FP, LQ), pp. 241–248.
RecSysRecSys-2014-TrevisiolASJ #recommendation
Cold-start news recommendation with domain-dependent browse graph (MT, LMA, RS, AJ), pp. 81–88.
SEKESEKE-2014-WanZWS #analysis #performance #points-to
Efficient Points-To Analysis for Partial Call Graph Construction (ZW, BZ, YW, YS), pp. 416–421.
SIGIRSIGIR-2014-GrausDTWR #communication #email #enterprise #recommendation #using
Recipient recommendation in enterprises using communication graphs and email content (DG, DvD, MT, WW, MdR), pp. 1079–1082.
SIGIRSIGIR-2014-YuM #named
Sig-SR: SimRank search over singular graphs (WY, JAM), pp. 859–862.
SIGIRSIGIR-2014-Zhang #rdf #scalability
Graph-based large scale RDF data compression (WEZ), p. 1276.
SIGIRSIGIR-2014-ZhangLLZ #evolution #multi #named
PatentLine: analyzing technology evolution on multi-view patent graphs (LZ, LL, TL, QZ), pp. 1095–1098.
ICMTICMT-2014-ErginS #design pattern #model transformation #towards
Towards a Language for Graph-Based Model Transformation Design Patterns (HE, ES), pp. 91–105.
MODELSMoDELS-2014-Bergmann #ocl
Translating OCL to Graph Patterns (GB), pp. 670–686.
SPLCSPLC-2014-AngererPLGG #dependence #identification #product line
Identifying inactive code in product lines with configuration-aware system dependence graphs (FA, HP, DL, AG, PG), pp. 52–61.
ECOOPECOOP-2014-AliRLDT #scala #source code
Constructing Call Graphs of Scala Programs (KA, MR, OL, JD, FT), pp. 54–79.
AdaEuropeAdaEurope-2014-QamhiehM #analysis #multi #scheduling
Schedulability Analysis for Directed Acyclic Graphs on Multiprocessor Systems at a Subtask Level (MQ, SM), pp. 119–133.
POPLPOPL-2014-BeyeneCPR #approach #constraints #game studies #infinity
A constraint-based approach to solving games on infinite graphs (TAB, SC, CP, AR), pp. 221–234.
FSEFSE-2014-JaffarM #control flow #slicing
A path-sensitively sliced control flow graph (JJ, VM), pp. 133–143.
FSEFSE-2014-NguyenKN #embedded #web
Building call graphs for embedded client-side code in dynamic web applications (HVN, CK, TNN), pp. 518–529.
FSEFSE-2014-XuanODF #congruence #developer
Focus-shifting patterns of OSS developers and their congruence with call graphs (QX, AO, PTD, VF), pp. 401–412.
ICSEICSE-2014-LeP #control flow #interprocedural #multi #verification
Patch verification via multiversion interprocedural control flow graphs (WL, SDP), pp. 1047–1058.
SACSAC-2014-MaAS
Project centralization based on graph coloring (LM, CA, HS), pp. 1086–1093.
SACSAC-2014-SaSCTMR #named
LEGi: context-aware lexicon consolidation by graph inspection (GS, TS, RC, FT, FM, LCdR), pp. 302–307.
SACSAC-2014-SeelandKK #clustering
Structural clustering of millions of molecular graphs (MS, AK, SK), pp. 121–128.
SLESLE-2014-Hills #control flow
Streamlining Control Flow Graph Construction with DCFlow (MH), pp. 322–341.
CASECASE-2014-HeLG #optimisation
Marking optimization of deterministic timed weighted marked graphs (ZH, ZL, AG), pp. 413–418.
CGOCGO-2014-HongSWO #domain-specific language #scalability
Simplifying Scalable Graph Processing with a Domain-Specific Language (SH, SS, JW, KO), p. 208.
DACDAC-2014-AmaruGM #algorithm #logic #novel #optimisation #performance
Majority-Inverter Graph: A Novel Data-Structure and Algorithms for Efficient Logic Optimization (LGA, PEG, GDM), p. 6.
DATEDATE-2014-ChenHD #analysis #modelling
May-happen-in-parallel analysis based on segment graphs for safe ESL models (WC, XH, RD), pp. 1–6.
DATEDATE-2014-FrijnsASVGSC #analysis
Timing analysis of First-Come First-Served scheduled interval-timed Directed Acyclic Graphs (RF, SA, SS, JV, MCWG, RRHS, HC), pp. 1–6.
DATEDATE-2014-ParkYLL #memory management #representation
Accelerating graph computation with racetrack memory and pointer-assisted graph representation (EP, SY, SL, HL), pp. 1–4.
DATEDATE-2014-ZhuGBS #data flow #scheduling
Memory-constrained static rate-optimal scheduling of synchronous dataflow graphs via retiming (XYZ, MG, TB, SS), pp. 1–6.
HPCAHPCA-2014-LakshminarayanaK #algorithm
Spare register aware prefetching for graph algorithms on GPUs (NBL, HK), pp. 614–625.
HPDCHPDC-2014-ChenDWCZG #communication #distributed #performance #perspective
Computation and communication efficient graph processing with distributed immutable view (RC, XD, PW, HC, BZ, HG), pp. 215–226.
HPDCHPDC-2014-KhorasaniVGB #named
CuSha: vertex-centric graph processing on GPUs (FK, KV, RG, LNB), pp. 239–252.
HPDCHPDC-2014-XueYQHD #concurrent #low cost #named #performance
Seraph: an efficient, low-cost system for concurrent graph processing (JX, ZY, ZQ, SH, YD), pp. 227–238.
ISMMISMM-2014-RatnakarN #analysis #constraints #performance #points-to
Push-pull constraint graph for efficient points-to analysis (BR, RN), pp. 25–33.
OSDIOSDI-2014-GonzalezXDCFS #data flow #distributed #framework #named
GraphX: Graph Processing in a Distributed Dataflow Framework (JEG, RSX, AD, DC, MJF, IS), pp. 599–613.
PDPPDP-2014-DalKT #performance #scalability #using
Fast Diameter Computation of Large Sparse Graphs Using GPUs (GHD, WAK, FWT), pp. 632–639.
PDPPDP-2014-KotenkoDC #game studies #metric #security
Security Metrics Based on Attack Graphs for the Olympic Games Scenario (IVK, ED, AC), pp. 561–568.
FASEFASE-2014-GomesPG #bytecode #control flow #java #source code
Sound Control Flow Graph Extraction from Incomplete Java Bytecode Programs (PdCG, AP, DG), pp. 215–229.
FoSSaCSFoSSaCS-2014-Lang #automaton #game studies #reachability
Resource Reachability Games on Pushdown Graphs (ML0), pp. 195–209.
STOCSTOC-2014-AbrahamGGNT #composition
Cops, robbers, and threatening skeletons: padded decomposition for minor-free graphs (IA, CG, AG, ON, KT), pp. 79–88.
STOCSTOC-2014-AndoniNOY #algorithm #geometry #parallel #problem
Parallel algorithms for geometric graph problems (AA, AN, KO, GY), pp. 574–583.
STOCSTOC-2014-ElberfeldK #bound
Embedding and canonizing graphs of bounded genus in logspace (ME, KiK), pp. 383–392.
STOCSTOC-2014-GroheKS #first-order
Deciding first-order properties of nowhere dense graphs (MG, SK, SS), pp. 89–98.
STOCSTOC-2014-HenzingerKN #algorithm #reachability
Sublinear-time decremental algorithms for single-source reachability and shortest paths on directed graphs (MH, SK, DN), pp. 674–683.
STOCSTOC-2014-KawarabayashiKK #grid #problem #theorem
An excluded half-integral grid theorem for digraphs and the directed disjoint paths problem (KiK, YK, SK), pp. 70–78.
TACASTACAS-2014-DudkaPV #contest #memory management #named
Predator: A Shape Analyzer Based on Symbolic Memory Graphs — (Competition Contribution) (KD, PP, TV), pp. 412–414.
CAVCAV-2014-WijsKB #component #composition
GPU-Based Graph Decomposition into Strongly Connected and Maximal End Components (AW, JPK, DB), pp. 310–326.
ICLPICLP-J-2014-CabalarFF #logic programming #source code
Causal Graph Justifications of Logic Programs (PC, JF, MF), pp. 603–618.
ICLPICLP-J-2014-CruzRGP #concurrent #linear #logic programming #programming language
A Linear Logic Programming Language for Concurrent Programming over Graph Structures (FC, RR, SCG, FP), pp. 493–507.
LICSLICS-CSL-2014-BarceloM #combinator #logic #word
Graph logics with rational relations: the role of word combinatorics (PB, PM), p. 10.
LICSLICS-CSL-2014-ChenM #classification #complexity #query
One hierarchy spawns another: graph deconstructions and the complexity classification of conjunctive queries (HC, MM), p. 10.
LICSLICS-CSL-2014-Williams #first-order #performance
Faster decision of first-order graph properties (RW), p. 6.
ECSAECSA-2013-GassaraRJ #architecture #deployment #modelling #multi #towards
Towards a Multi-scale Modeling for Architectural Deployment Based on Bigraphs (AG, IBR, MJ), pp. 122–129.
DocEngDocEng-2013-SrivastavaSM #interactive #topic
A graph-based topic extraction method enabling simple interactive customization (AS, AJS, EEM), pp. 71–80.
DRRDRR-2013-ZanibbiMV #pattern matching #pattern recognition #recognition
Evaluating structural pattern recognition for handwritten math via primitive label graphs (RZ, HM, CVG).
HTHT-2013-LeginusDL #generative
Graph based techniques for tag cloud generation (ML, PD, RL), pp. 148–157.
ICDARICDAR-2013-0001LBP #approximate #documentation #string #visual notation
Near Convex Region Adjacency Graph and Approximate Neighborhood String Matching for Symbol Spotting in Graphical Documents (AD, JL, HB, UP), pp. 1078–1082.
ICDARICDAR-2013-GotoIFU #scalability #set #using
Analyzing the Distribution of a Large-Scale Character Pattern Set Using Relative Neighborhood Graph (MG, RI, YF, SU), pp. 3–7.
ICDARICDAR-2013-HerzogSN #retrieval #using
Using Harris Corners for the Retrieval of Graphs in Historical Manuscripts (RH, AS, BN), pp. 1295–1299.
JCDLJCDL-2013-GollapalliMG #ranking #topic #using
Ranking experts using author-document-topic graphs (SDG, PM, CLG), pp. 87–96.
PODSPODS-2013-Baeza #database #query
Querying graph databases (PBB), pp. 175–188.
PODSPODS-2013-BaezaRV #database #semantics
Semantic acyclicity on graph databases (PBB, MR, MYV), pp. 237–248.
PODSPODS-2013-BaganBG #query
A trichotomy for regular simple path queries on graphs (GB, AB, BG), pp. 261–272.
PODSPODS-2013-LibkinRV #adaptation #query #rdf
Trial for RDF: adapting graph query languages for RDF data (LL, JLR, DV), pp. 201–212.
SIGMODSIGMOD-2013-ArmstrongPBC #benchmark #database #facebook #metric #named #social
LinkBench: a database benchmark based on the Facebook social graph (TGA, VP, DB, MC), pp. 1185–1196.
SIGMODSIGMOD-2013-ChangYQLLL #component #composition
Efficiently computing k-edge connected components via graph decomposition (LC, JXY, LQ, XL, CL, WL), pp. 205–216.
SIGMODSIGMOD-2013-ChengHWF #named #query #reachability #scalability
TF-Label: a topological-folding labeling scheme for reachability querying in a large graph (JC, SH, HW, AWCF), pp. 193–204.
SIGMODSIGMOD-2013-ChoudhuryHCRBF #named
StreamWorks: a system for dynamic graph search (SC, LBH, GCJ, AR, SB, JF), pp. 1101–1104.
SIGMODSIGMOD-2013-HanLL #database #morphism #named #robust #scalability #towards
Turboiso: towards ultrafast and robust subgraph isomorphism search in large graph databases (WSH, JL, JHL), pp. 337–348.
SIGMODSIGMOD-2013-HuTC
Massive graph triangulation (XH, YT, CWC), pp. 325–336.
SIGMODSIGMOD-2013-ShaoWL #distributed #memory management #named
Trinity: a distributed graph engine on a memory cloud (BS, HW, YL), pp. 505–516.
SIGMODSIGMOD-2013-ZhangYQCL #performance
I/O efficient: computing SCCs in massive graphs (ZZ, JXY, LQ, LC, XL), pp. 181–192.
SIGMODSIGMOD-2013-ZhuZQ #approach #mining #performance
A direct mining approach to efficient constrained graph pattern discovery (FZ, ZZ, QQ), pp. 821–832.
TPDLTPDL-2013-BikakisGLSDS #keyword #named #rdf
RDivF: Diversifying Keyword Search on RDF Graphs (NB, GG, JL, DS, TD, TKS), pp. 413–416.
VLDBVLDB-2013-0007TR #effectiveness #keyword #performance #probability #query
Probabilistic Query Rewriting for Efficient and Effective Keyword Search on Graph Data (LZ, TT, AR), pp. 1642–1653.
VLDBVLDB-2013-BambaRHA #geometry #performance #statistics
Statistics Collection in Oracle Spatial and Graph: Fast Histogram Construction for Complex Geometry Objects (BB, SR, YH, RA), pp. 1021–1032.
VLDBVLDB-2013-CurtissBBDGJKLPSSWYZ #named #social
Unicorn: A System for Searching the Social Graph (MC, IB, TB, SD, LG, TJ, SK, SL, PP, SS, GS, GW, CY, NZ), pp. 1150–1161.
VLDBVLDB-2013-FanWW #pattern matching
Diversified Top-k Graph Pattern Matching (WF, XW, YW), pp. 1510–1521.
VLDBVLDB-2013-KhanWAY #named #performance #similarity
NeMa: Fast Graph Search with Label Similarity (AK, YW, CCA, XY), pp. 181–192.
VLDBVLDB-2013-LeeL #clustering #query #rdf #scalability #semantics
Scaling Queries over Big RDF Graphs with Semantic Hash Partitioning (KL, LL), pp. 1894–1905.
VLDBVLDB-2013-PavanTTW
Counting and Sampling Triangles from a Graph Stream (AP, KT, ST, KLW), pp. 1870–1881.
VLDBVLDB-2013-QiaoQCYT #keyword #scalability
Top-K Nearest Keyword Search on Large Graphs (MQ, LQ, HC, JXY, WT), pp. 901–912.
VLDBVLDB-2013-SarwatEHM #declarative #distributed #query #reachability
Horton+: A Distributed System for Processing Declarative Reachability Queries over Partitioned Graphs (MS, SE, YH, MFM), pp. 1918–1929.
VLDBVLDB-2013-SeoPSL #analysis #distributed #scalability
Distributed SociaLite: A Datalog-Based Language for Large-Scale Graph Analysis (JS, JP, JS, MSL), pp. 1906–1917.
VLDBVLDB-2013-ShkapskyZZ #datalog #query
Graph Queries in a Next-Generation Datalog System (AS, KZ, CZ), pp. 1258–1261.
VLDBVLDB-2013-WuYSIY #keyword #query
Summarizing Answer Graphs Induced by Keyword Queries (YW, SY, MS, AI, XY), pp. 1774–1785.
VLDBVLDB-2013-XieWBDG #performance
Fast Iterative Graph Computation with Block Updates (WX, GW, DB, AJD, JG), pp. 2014–2025.
VLDBVLDB-2013-YuanMG #mining
Mining and Indexing Graphs for Supergraph Search (DY, PM, CLG), pp. 829–840.
VLDBVLDB-2013-ZengYWSW #distributed #rdf #web
A Distributed Graph Engine for Web Scale RDF Data (KZ, JY, HW, BS, ZW), pp. 265–276.
VLDBVLDB-2013-ZhengZF0Z #performance #scalability #similarity
Efficient SimRank-based Similarity Join Over Large Graphs (WZ, LZ, YF, LC, DZ), pp. 493–504.
VLDBVLDB-2013-ZhongH #parallel
Parallel Graph Processing on Graphics Processors Made Easy (JZ, BH), pp. 1270–1273.
VLDBVLDB-2014-QiXSW13 #distance #towards
Toward a Distance Oracle for Billion-Node Graphs (ZQ, YX, BS, HW), pp. 61–72.
VLDBVLDB-2014-TianBCTM13
From “Think Like a Vertex” to “Think Like a Graph” (YT, AB, SAC, ST, JM), pp. 193–204.
ICPCICPC-2013-FalconeS #diagrams #eclipse #named #plugin #uml #visualisation
OnionUML: An Eclipse plug-in for visualizing UML class diagrams in onion graph notation (MF, BS), pp. 233–235.
MSRMSR-2013-WagstromJS #dataset #network #ruby
A network of rails: a graph dataset of ruby on rails and associated projects (PW, CJ, AS), pp. 229–232.
WCREWCRE-2013-BernardiCL #approach #design pattern #detection #modelling
A model-driven graph-matching approach for design pattern detection (MLB, MC, GADL), pp. 172–181.
DLTDLT-2013-LibkinTV #database #query #regular expression #word
Regular Expressions with Binding over Data Words for Querying Graph Databases (LL, TT, DV), pp. 325–337.
ICALPICALP-v1-2013-BlasiusRW #orthogonal
Optimal Orthogonal Graph Drawing with Convex Bend Costs (TB, IR, DW), pp. 184–195.
ICALPICALP-v1-2013-BringmannF #generative #geometry #performance #random
Exact and Efficient Generation of Geometric Random Variates and Random Graphs (KB, TF), pp. 267–278.
ICALPICALP-v1-2013-ChekuriNS
Maximum Edge-Disjoint Paths in k-Sums of Graphs (CC, GN, FBS), pp. 328–339.
ICALPICALP-v1-2013-CyganP #algorithm #bound #performance
Faster Exponential-Time Algorithms in Graphs of Bounded Average Degree (MC, MP), pp. 364–375.
ICALPICALP-v1-2013-Lampis #bound #model checking
Model Checking Lower Bounds for Simple Graphs (ML), pp. 673–683.
ICALPICALP-v1-2013-LauriaPRT #complexity #proving
The Complexity of Proving That a Graph Is Ramsey (ML, PP, VR, NT), pp. 684–695.
ICALPICALP-v1-2013-LeviR
A Quasi-Polynomial Time Partition Oracle for Graphs with an Excluded Minor (RL, DR), pp. 709–720.
ICALPICALP-v1-2013-MathieuZ #distance #re-engineering
Graph Reconstruction via Distance Oracles (CM, HZ), pp. 733–744.
ICALPICALP-v1-2013-WeimannY #approximate #linear
Approximating the Diameter of Planar Graphs in Near Linear Time (OW, RY), pp. 828–839.
ICALPICALP-v2-2013-DereniowskiDKPU #collaboration #performance
Fast Collaborative Graph Exploration (DD, YD, AK, DP, PU), pp. 520–532.
ICALPICALP-v2-2013-GanianHKOST #model checking
FO Model Checking of Interval Graphs (RG, PH, DK, JO, JS, JT), pp. 250–262.
ICALPICALP-v2-2013-HartungNNS #analysis #complexity
A Refined Complexity Analysis of Degree Anonymization in Graphs (SH, AN, RN, OS), pp. 594–606.
ICALPICALP-v2-2013-Marx
The Square Root Phenomenon in Planar Graphs (DM), p. 28.
ICALPICALP-v2-2013-PettieS #algorithm #distributed #performance
Fast Distributed Coloring Algorithms for Triangle-Free Graphs (SP, HHS), pp. 681–693.
ICALPICALP-v2-2013-SpirakisNR #random
A Guided Tour in Random Intersection Graphs (PGS, SEN, CR), pp. 29–35.
LATALATA-2013-AlurKTY #complexity #on the #problem
On the Complexity of Shortest Path Problems on Discounted Cost Graphs (RA, SK, KT, YY), pp. 44–55.
LATALATA-2013-Blanchet-SadriBFH #approach #polynomial
A Graph Polynomial Approach to Primitivity (FBS, MB, NF, JH), pp. 153–164.
ICFPICFP-2013-HidakaAHKN #order #query #recursion
Structural recursion for querying ordered graphs (SH, KA, ZH, HK, KN), pp. 305–318.
CoGCIG-2013-Brown #multi #network #search-based
Examination of graphs in Multiple Agent Genetic Networks for Iterated Prisoner's Dilemma (JAB), pp. 1–8.
GCMGCM-J-2012-FaithfullPH #development
Big Red: A Development Environment for Bigraphs (AJF, GP, TTH).
GCMGCM-J-2012-MantzTL #co-evolution
Co-Transformation of Type and Instance Graphs Supporting Merging of Types and Retyping (FM, GT, YL).
GCMGCM-J-2012-PoskittP #correctness #source code #verification
Verifying Total Correctness of Graph Programs (CMP, DP).
GCMGCM-J-2012-Radke #higher-order #monad
HR* Graph Conditions Between Counting Monadic Second-Order and Second-Order Graph Formulas (HR).
CHICHI-2013-AlperBRIF #analysis #comparison
Weighted graph comparison techniques for brain connectivity analysis (BA, BB, NHR, TI, JDF), pp. 483–492.
CHICHI-2013-PerinVF #interactive #multi #visualisation
Interactive horizon graphs: improving the compact visualization of multiple time series (CP, FV, JDF), pp. 3217–3226.
HCIDUXU-WM-2013-Rafelsberger #evolution #interactive #visualisation
Interactive Visualization of Evolving Force-Directed Graphs (WR), pp. 553–559.
HCIHCI-UC-2013-KuramochiOTHN #analysis #community #network #semantics #twitter #using
Applying to Twitter Networks of a Community Extraction Method Using Intersection Graph and Semantic Analysis (TK, NO, KT, YH, SN), pp. 314–323.
EDOCEDOC-2013-MukkamalaHS #adaptation #towards
Towards Trustworthy Adaptive Case Management with Dynamic Condition Response Graphs (RRM, TTH, TS), pp. 127–136.
EDOCEDOC-2013-PlataniotisKP #architecture #design #enterprise #using
Relating Decisions in Enterprise Architecture Using Decision Design Graphs (GP, SdK, HAP), pp. 139–146.
ICEISICEIS-J-2013-SuB13a #fine-grained #identification #security
Foundation for Fine-Grained Security and DRM Control Based on a Service Call Graph Context Identification (ZS, FB), pp. 226–241.
ICEISICEIS-v2-2013-SuB #analysis #composition #data flow #web #web service
Service Call Graph (SCG) — Information Flow Analysis in Web Service Composition (ZS, FB), pp. 17–24.
CIKMCIKM-2013-ChanLKLBR #matrix #using
Discovering latent blockmodels in sparse and noisy graphs using non-negative matrix factorisation (JC, WL, AK, CL, JB, KR), pp. 811–816.
CIKMCIKM-2013-FangYZ #scalability
Active exploration: simultaneous sampling and labeling for large graphs (MF, JY, XZ), pp. 829–834.
CIKMCIKM-2013-FiondaP #query
Querying graphs with preferences (VF, GP), pp. 929–938.
CIKMCIKM-2013-GuoZ #classification #comprehension #empirical #perspective
Understanding the roles of sub-graph features for graph classification: an empirical study perspective (TG, XZ), pp. 817–822.
CIKMCIKM-2013-HanW #mining #scalability
Mining frequent neighborhood patterns in a large labeled graph (JH, JRW), pp. 259–268.
CIKMCIKM-2013-HermanssonKJJD #ambiguity #kernel #using
Entity disambiguation in anonymized graphs using graph kernels (LH, TK, FJ, VJ, DPD), pp. 1037–1046.
CIKMCIKM-2013-LuoFHWB #bisimulation #memory management #reduction
External memory K-bisimulation reduction of big graphs (YL, GHLF, JH, YW, PDB), pp. 919–928.
CIKMCIKM-2013-MackoMS #clustering
Local clustering in provenance graphs (PM, DWM, MIS), pp. 835–840.
CIKMCIKM-2013-MalliarosV #modelling #social
To stay or not to stay: modeling engagement dynamics in social graphs (FDM, MV), pp. 469–478.
CIKMCIKM-2013-ParkC #algorithm #performance #pipes and filters #scalability
An efficient MapReduce algorithm for counting triangles in a very large graph (HMP, CWC), pp. 539–548.
CIKMCIKM-2013-ShaoYCM #named
PAGE: a partition aware graph computation engine (YS, JY, BC, LM), pp. 823–828.
CIKMCIKM-2013-TangwongsanPT #parallel #streaming
Parallel triangle counting in massive streaming graphs (KT, AP, ST), pp. 781–786.
CIKMCIKM-2013-WangLZ #approach #metric #multi #random #towards
Towards metric fusion on multi-view data: a cross-view based graph random walk approach (YW, XL, QZ), pp. 805–810.
CIKMCIKM-2013-YuanWJL #clustering #performance #streaming
Efficient processing of streaming graphs for evolution-aware clustering (MY, KLW, GJS, YL), pp. 319–328.
CIKMCIKM-2013-ZhangKGCZH
Map search via a factor graph model (QZ, JK, YG, HC, YZ, XH), pp. 69–78.
ECIRECIR-2013-CarpinetoR #concept #query #semantics
Semantic Search Log k-Anonymization with Generalized k-Cores of Query Concept Graph (CC, GR), pp. 110–121.
ECIRECIR-2013-ZhuGCLN #query #recommendation
Recommending High Utility Query via Session-Flow Graph (XZ, JG, XC, YL, WN), pp. 642–655.
ICMLICML-c1-2013-KumarB #bound #learning
Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs (KSSK, FRB), pp. 525–533.
ICMLICML-c2-2013-Tran-DinhKC #framework #learning #matrix
A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions (QTD, ATK, VC), pp. 271–279.
ICMLICML-c3-2013-AilonCX #clustering
Breaking the Small Cluster Barrier of Graph Clustering (NA, YC, HX), pp. 995–1003.
KDDKDD-2013-AnchuriZBGS #approximate #mining
Approximate graph mining with label costs (PA, MJZ, OB, SG, MS), pp. 518–526.
KDDKDD-2013-ChengZGWSW #clustering #flexibility #multi #robust
Flexible and robust co-regularized multi-domain graph clustering (WC, XZ, ZG, YW, PFS, WW), pp. 320–328.
KDDKDD-2013-FriezeGT #algorithm #mining #modelling #scalability
Algorithmic techniques for modeling and mining large graphs (AMAzING) (AMF, AG, CET), p. 1523.
KDDKDD-2013-GuALH #classification
Selective sampling on graphs for classification (QG, CCA, JL, JH), pp. 131–139.
KDDKDD-2013-HanLPL0KY #named #parallel #performance
TurboGraph: a fast parallel graph engine handling billion-scale graphs in a single PC (WSH, SL, KP, JHL, MSK, JK, HY), pp. 77–85.
KDDKDD-2013-MorenoNK #learning #modelling
Learning mixed kronecker product graph models with simulated method of moments (SM, JN, SK), pp. 1052–1060.
KDDKDD-2013-NishimuraU #algorithm #clustering
Restreaming graph partitioning: simple versatile algorithms for advanced balancing (JN, JU), pp. 1106–1114.
KDDKDD-2013-ShenY #difference #mining #privacy
Mining frequent graph patterns with differential privacy (ES, TY), pp. 545–553.
KDDKDD-2013-UganderKBK #clustering #multi #network
Graph cluster randomization: network exposure to multiple universes (JU, BK, LB, JMK), pp. 329–337.
KDDKDD-2013-WangGS
Active search on graphs (XW, RG, JGS), pp. 731–738.
KDDKDD-2013-ZhuXWL #distance #performance #query #scalability
Efficient single-source shortest path and distance queries on large graphs (ADZ, XX, SW, WL), pp. 998–1006.
RecSysRecSys-2013-AhnPLL #recommendation
A heterogeneous graph-based recommendation simulator (YA, SP, SL, SgL), pp. 471–472.
RecSysRecSys-2013-BlankRS #keyword #recommendation
Leveraging the citation graph to recommend keywords (IB, LR, GS), pp. 359–362.
RecSysRecSys-2013-Shi #approach #recommendation #similarity
Trading-off among accuracy, similarity, diversity, and long-tail: a graph-based recommendation approach (LS), pp. 57–64.
RecSysRecSys-2013-TianJ #recommendation #using
Recommending scientific articles using bi-relational graph-based iterative RWR (GT, LJ), pp. 399–402.
SEKESEKE-2013-CorreaOW #co-evolution #evolution #metamodelling #modelling #towards #traceability
Towards Coupled Evolution of Metamodels, Models, Graph-Based Transformations and Traceability Links (CKFC, TCO, CW), pp. 747–752.
SEKESEKE-2013-LiLJJ #communication #comprehension #concurrent #debugging
Locating and Understanding Concurrency Bugs Based on Edge-labeled Communication Graphs (HL, ML, TJ, ZJ), pp. 525–530.
SIGIRSIGIR-2013-FreitasFOC #approach #linked data #natural language #open data #query #semantics
Answering natural language queries over linked data graphs: a distributional semantics approach (AF, FFdF, SO, EC), pp. 1107–1108.
MODELSMoDELS-2013-SemerathHV #constraints #domain-specific language #query #validation
Validation of Derived Features and Well-Formedness Constraints in DSLs — By Mapping Graph Queries to an SMT-Solver (OS, ÁH, DV), pp. 538–554.
ECOOPECOOP-2013-AuerbachBCFR #compilation #configuration management #hardware
The Shape of Things to Run — Compiling Complex Stream Graphs to Reconfigurable Hardware in Lime (JSA, DFB, PC, SF, RMR), pp. 679–706.
ECOOPECOOP-2013-CoxCS #generative #invariant #relational
QUIC Graphs: Relational Invariant Generation for Containers (AC, BYEC, SS), pp. 401–425.
OOPSLAOOPSLA-2013-BalatsourasS
Class hierarchy complementation: soundly completing a partial type graph (GB, YS), pp. 515–532.
OOPSLAOOPSLA-2013-BoisSEE #concurrent #multi #scalability #thread #visualisation
Bottle graphs: visualizing scalability bottlenecks in multi-threaded applications (KDB, JBS, SE, LE), pp. 355–372.
PEPMPEPM-2013-OliveiraL #domain-specific language #syntax
Abstract syntax graphs for domain specific languages (BCdSO, AL), pp. 87–96.
PLDIPLDI-2013-JohnsonOZA #dependence #performance
Fast condensation of the program dependence graph (NPJ, TO, AZ, DIA), pp. 39–50.
POPLPOPL-2013-FarzanKP #data flow #induction
Inductive data flow graphs (AF, ZK, AP), pp. 129–142.
PPDPPPDP-2013-AsadaHKHN #branch #calculus #finite #graph transformation #monad
A parameterized graph transformation calculus for finite graphs with monadic branches (KA, SH, HK, ZH, KN), pp. 73–84.
PPDPPPDP-2013-LamoMRL #approach #bidirectional #declarative #model transformation
A declarative and bidirectional model transformation approach based on graph co-spans (YL, FM, AR, JdL), pp. 1–12.
ASEASE-2013-IzsoSBHR #metric #performance #precise #predict #query #towards
Towards precise metrics for predicting graph query performance (BI, ZS, GB, ÁH, IR), pp. 421–431.
ICSEICSE-2013-FeldthausSSDT #approximate #ide #javascript #performance
Efficient construction of approximate call graphs for JavaScript IDE services (AF, MS, MS, JD, FT), pp. 752–761.
SACSAC-2013-HassanzadehN #algorithm #detection
A semi-supervised graph-based algorithm for detecting outliers in online-social-networks (RH, RN), pp. 577–582.
SACSAC-2013-LiZSL #approach #mining #named #novel
WAVE-CIA: a novel CIA approach based on call graph mining (BL, QZ, XS, HL), pp. 1000–1005.
SACSAC-2013-MaunzVH #mining
Out-of-bag discriminative graph mining (AM, DV, CH), pp. 109–114.
SACSAC-2013-SeelandKP #kernel #learning
Model selection based product kernel learning for regression on graphs (MS, SK, BP), pp. 136–143.
SACSAC-2013-Serafino #clustering #composition
Speeding up graph clustering via modular decomposition based compression (PS), pp. 156–163.
SACSAC-2013-SrivastavaSM #clustering #using
Text clustering using one-mode projection of document-word bipartite graphs (AS, AJS, EEM), pp. 927–932.
CASECASE-2013-LuSXPO #automation #multi #using
Automatic building exterior mapping using multilayer feature graphs (YL, DS, YX, AGAP, SO), pp. 162–167.
CGOCGO-2013-YanTZYS #algorithm #fine-grained #named #parallel #traversal
Vlock: Lock virtualization mechanism for exploiting fine-grained parallelism in graph traversal algorithms (JY, GT, XZ, EY, NS), p. 10.
DACDAC-2013-BenazouzKHB #data flow #evaluation #liveness
Liveness evaluation of a cyclo-static DataFlow graph (MB, AMK, TH, BB), p. 7.
DATEDATE-2013-Pomeranz #equivalence #fault #on the #set
On candidate fault sets for fault diagnosis and dominance graphs of equivalence classes (IP), pp. 1083–1088.
ISMMISMM-2013-LiCK #analysis #pointer #precise #scalability
Precise and scalable context-sensitive pointer analysis via value flow graph (LL, CC, NK), pp. 85–96.
LCTESLCTES-2013-BouakazT #data flow #scheduling
Buffer minimization in earliest-deadline first scheduling of dataflow graphs (AB, JPT), pp. 133–142.
LCTESLCTES-2013-HuberPP #analysis #control flow #using
Combined WCET analysis of bitcode and machine code using control-flow relation graphs (BH, DP, PPP), pp. 163–172.
PPoPPPPoPP-2013-EdmondsWL #algorithm #using
Expressing graph algorithms using generalized active messages (NE, JW, AL), pp. 289–290.
PPoPPPPoPP-2013-ShunB #framework #lightweight #memory management #named
Ligra: a lightweight graph processing framework for shared memory (JS, GEB), pp. 135–146.
SOSPSOSP-2013-NguyenLP #framework #lightweight
A lightweight infrastructure for graph analytics (DN, AL, KP), pp. 456–471.
SOSPSOSP-2013-RoyMZ #named #streaming #using
X-Stream: edge-centric graph processing using streaming partitions (AR, IM, WZ), pp. 472–488.
FoSSaCSFoSSaCS-2013-HaymanH #modelling #rule-based #semantics
Pattern Graphs and Rule-Based Models: The Semantics of Kappa (JH, TH), pp. 1–16.
STOCSTOC-2013-Bernstein #maintenance
Maintaining shortest paths under deletions in weighted directed graphs: [extended abstract] (AB), pp. 725–734.
STOCSTOC-2013-ChekuriC
Large-treewidth graph decompositions and applications (CC, JC), pp. 291–300.
STOCSTOC-2013-EisenstatK #algorithm #linear #multi
Linear-time algorithms for max flow and multiple-source shortest paths in unit-weight planar graphs (DE, PNK), pp. 735–744.
STOCSTOC-2013-GuptaTW #algorithm #bound
Sparsest cut on bounded treewidth graphs: algorithms and hardness results (AG, KT, DW), pp. 281–290.
STOCSTOC-2013-KawarabayashiY #testing
Testing subdivision-freeness: property testing meets structural graph theory (KiK, YY), pp. 437–446.
STOCSTOC-2013-KleinMS #linear #recursion
Structured recursive separator decompositions for planar graphs in linear time (PNK, SM, CS), pp. 505–514.
STOCSTOC-2013-Miller #optimisation #problem #scalability #using
Solving large optimization problems using spectral graph theory (GLM), p. 981.
STOCSTOC-2013-RodittyW #algorithm #approximate #performance
Fast approximation algorithms for the diameter and radius of sparse graphs (LR, VVW), pp. 515–524.
CAVCAV-2013-HaaseIOP #logic #named #reasoning
SeLoger: A Tool for Graph-Based Reasoning in Separation Logic (CH, SI, JO, MJP), pp. 790–795.
LICSLICS-2013-EickmeyerKK #first-order #invariant #logic #model checking
Model Checking for Successor-Invariant First-Order Logic on Minor-Closed Graph Classes (KE, KiK, SK), pp. 134–142.
ICSTSAT-2013-Toran #complexity #morphism #on the
On the Resolution Complexity of Graph Non-isomorphism (JT), pp. 52–66.
QoSAQoSA-2012-Abi-AntounAH #case study #experience #object-oriented
Extraction of ownership object graphs from object-oriented code: an experience report (MAA, NA, ZH), pp. 133–142.
DocEngDocEng-2012-ChuangW #documentation #morphism #xml
Structure-conforming XML document transformation based on graph homomorphism (TRC, HYW), pp. 99–102.
HTHT-2012-ChairunnandaFD #modelling #network #online #social
Graph data partition models for online social networks (PC, SF, KD), pp. 175–180.
HTHT-2012-KontopoulouPKG #matrix #metric
Graph and matrix metrics to analyze ergodic literature for children (EMK, MP, TK, EG), pp. 133–142.
PODSPODS-2012-AhnGM #sketching
Graph sketches: sparsification, spanners, and subgraphs (KJA, SG, AM), pp. 5–14.
PODSPODS-2012-ChoromanskiM #algorithm #database #power of #privacy #statistics
The power of the dinur-nissim algorithm: breaking privacy of statistical and graph databases (KC, TM), pp. 65–76.
SIGMODSIGMOD-2012-AkogluCKKF #mining #named #scalability #visualisation
OPAvion: mining and visualization in large graphs (LA, DHC, UK, DK, CF), pp. 717–720.
SIGMODSIGMOD-2012-AndersonTBRV #named
PAnG: finding patterns in annotation graphs (PA, AT, JB, LR, MEV), pp. 677–680.
SIGMODSIGMOD-2012-ChengKCC #approach #distance #performance #query #scalability
Efficient processing of distance queries in large graphs: a vertex cover approach (JC, YK, SC, CC), pp. 457–468.
SIGMODSIGMOD-2012-FaloutsosK #algorithm #mining #scalability
Managing and mining large graphs: patterns and algorithms (CF, UK), pp. 585–588.
SIGMODSIGMOD-2012-FanLWW #query
Query preserving graph compression (WF, JL, XW, YW), pp. 157–168.
SIGMODSIGMOD-2012-HellingsFH #bisimulation #performance
Efficient external-memory bisimulation on DAGs (JH, GHLF, HJH), pp. 553–564.
SIGMODSIGMOD-2012-JinRDY #named #reachability #scalability
SCARAB: scaling reachability computation on large graphs (RJ, NR, SD, JXY), pp. 169–180.
SIGMODSIGMOD-2012-JinRXL #approach #distance #query #scalability
A highway-centric labeling approach for answering distance queries on large sparse graphs (RJ, NR, YX, VEL), pp. 445–456.
SIGMODSIGMOD-2012-MondalD #scalability
Managing large dynamic graphs efficiently (JM, AD), pp. 145–156.
SIGMODSIGMOD-2012-ShaoWX #implementation #mining #scalability
Managing and mining large graphs: systems and implementations (BS, HW, YX), pp. 589–592.
SIGMODSIGMOD-2012-VenkataramaniABCCDDFGHKLMPP #facebook #how #named #social
TAO: how facebook serves the social graph (VV, ZA, NB, GCI, PC, PD, HD, JF, AG, JH, SK, NL, MM, DP, LP), pp. 791–792.
SIGMODSIGMOD-2012-XuKWCC #approach #clustering #modelling
A model-based approach to attributed graph clustering (ZX, YK, YW, HC, JC), pp. 505–516.
SIGMODSIGMOD-2012-YangYZK #effectiveness #scalability #towards
Towards effective partition management for large graphs (SY, XY, BZ, AK), pp. 517–528.
VLDBVLDB-2012-AgarwalRB #clustering #identification #realtime
Real Time Discovery of Dense Clusters in Highly Dynamic Graphs: Identifying Real World Events in Highly Dynamic Environments (MKA, KR, MB), pp. 980–991.
VLDBVLDB-2012-BoldiBGT #injection #nondeterminism #obfuscation
Injecting Uncertainty in Graphs for Identity Obfuscation (PB, FB, AG, TT), pp. 1376–1387.
VLDBVLDB-2012-GuanYK #correlation
Measuring Two-Event Structural Correlations on Graphs (ZG, XY, LMK), pp. 1400–1411.
VLDBVLDB-2012-GuhaM #overview #sketching
Graph Synopses, Sketches, and Streams: A Survey (SG, AM), pp. 2030–2031.
VLDBVLDB-2012-PrakashF #comprehension #scalability
Understanding and Managing Cascades on Large Graphs (BAP, CF), pp. 2024–2025.
VLDBVLDB-2012-SilvaMZ #correlation #mining #scalability
Mining Attribute-structure Correlated Patterns in Large Attributed Graphs (AS, WMJ, MJZ), pp. 466–477.
VLDBVLDB-2012-SunWWSL #performance
Efficient Subgraph Matching on Billion Node Graphs (ZS, HW, HW, BS, JL), pp. 788–799.
VLDBVLDB-2012-YuanWCW #database #performance #probability #scalability #similarity
Efficient Subgraph Similarity Search on Large Probabilistic Graph Databases (YY, GW, LC, HW), pp. 800–811.
VLDBVLDB-2012-ZengH #algorithm #pattern matching
Comments on “Stack-based Algorithms for Pattern Matching on DAGs” (QZ, HZ), pp. 668–679.
VLDBVLDB-2013-CalvaneseGLV12 #database #query #relational
Query Processing under GLAV Mappings for Relational and Graph Databases (DC, GDG, ML, MYV), pp. 61–72.
VLDBVLDB-2013-LeeHKL12 #algorithm #comparison #database #morphism
An In-depth Comparison of Subgraph Isomorphism Algorithms in Graph Databases (JL, WSH, RK, JHL), pp. 133–144.
ITiCSEITiCSE-2012-Gibson #algorithm #education
Teaching graph algorithms to children of all ages (JPG), pp. 34–39.
CSMRCSMR-2012-HottaHK #dependence #identification #refactoring
Identifying, Tailoring, and Suggesting Form Template Method Refactoring Opportunities with Program Dependence Graph (KH, YH, SK), pp. 53–62.
WCREWCRE-2012-TeytonFB #library #migration #mining
Mining Library Migration Graphs (CT, JRF, XB), pp. 289–298.
WCREWCRE-2012-VanciuA #data flow
Ownership Object Graphs with Dataflow Edges (RV, MAA), pp. 267–276.
ICALPICALP-v1-2012-ChekuriEV #design #network #product line
Node-Weighted Network Design in Planar and Minor-Closed Families of Graphs (CC, AE, AV), pp. 206–217.
ICALPICALP-v1-2012-CyganKPPW #clique
Clique Cover and Graph Separation: New Incompressibility Results (MC, SK, MP, MP, MW), pp. 254–265.
ICALPICALP-v1-2012-FeigeJ
Universal Factor Graphs (UF, SJ), pp. 339–350.
ICALPICALP-v1-2012-JefferyKM #complexity #matrix #multi #quantum #query #using
Improving Quantum Query Complexity of Boolean Matrix Multiplication Using Graph Collision (SJ, RK, FM), pp. 522–532.
ICALPICALP-v1-2012-KratschPPW #multi #parametricity
Fixed-Parameter Tractability of Multicut in Directed Acyclic Graphs (SK, MP, MP, MW), pp. 581–593.
ICALPICALP-v2-2012-ArrighiD
Causal Graph Dynamics (PA, GD), pp. 54–66.
ICALPICALP-v2-2012-Elbassioni
A QPTAS for ε-Envy-Free Profit-Maximizing Pricing on Line Graphs (KME), pp. 513–524.
ICALPICALP-v2-2012-GugelmannPP #clustering #random #sequence
Random Hyperbolic Graphs: Degree Sequence and Clustering — (LG, KP, UP), pp. 573–585.
ICALPICALP-v2-2012-KosowskiLNS
k-Chordal Graphs: From Cops and Robber to Compact Routing via Treewidth (AK, BL, NN, KS), pp. 610–622.
ICALPICALP-v2-2012-Spielman #algorithm #equation #linear
Algorithms, Graph Theory, and the Solution of Laplacian Linear Equations (DAS), pp. 24–26.
LATALATA-2012-MiasnikovS #automation
Cayley Graph Automatic Groups Are Not Necessarily Cayley Graph Biautomatic (AM, ZS), pp. 401–407.
SEFMSEFM-2012-AmighiGGH #control flow #exception #java #source code
Sound Control-Flow Graph Extraction for Java Programs with Exceptions (AA, PdCG, DG, MH), pp. 33–47.
ICFPICFP-2012-OliveiraC #functional #programming
Functional programming with structured graphs (BCdSO, WRC), pp. 77–88.
GRAPHITEGRAPHITE-2012-BeckmannFKM #analysis
A structural analysis of the A5/1 state transition graph (AB, JF, JK, UM), pp. 5–19.
GRAPHITEGRAPHITE-2012-ZambonR
Graph Subsumption in Abstract State Space Exploration (EZ, AR), pp. 35–49.
GT-VMTGT-VMT-2012-BottoniP #modelling
Modeling context with graph annotations (PB, FPP).
GT-VMTGT-VMT-2012-BrugginkHK #automaton #towards
Towards Alternating Automata for Graph Languages (HJSB, MH, BK).
GT-VMTGT-VMT-2012-Heussner #communication #graph grammar #model checking #process
Model Checking Communicating Processes: Run Graphs, Graph Grammars, and MSO (AH).
GT-VMTGT-VMT-2012-NatschlagerS #algebra #approach #graph transformation #inheritance
A Flattening Approach for Attributed Type Graphs with Inheritance in Algebraic Graph Transformation (CN, KDS).
GT-VMTGT-VMT-2012-Taentzer #generative #multi
Instance Generation from Type Graphs with Arbitrary Multiplicities (GT).
ICGTICGT-2012-BlumeBEK #automaton #implementation #invariant #performance
Efficient Symbolic Implementation of Graph Automata with Applications to Invariant Checking (CB, HJSB, DE, BK), pp. 264–278.
ICGTICGT-2012-LopesF #design #framework
A Graph-Based Design Framework for Services (AL, JLF), pp. 1–19.
ICGTICGT-2012-OrejasBM
Borrowed Contexts for Attributed Graphs (FO, AB, NM), pp. 126–140.
ICGTICGT-2012-Poskitt #source code #verification
Verification of Graph Programs (CMP), pp. 420–422.
ICGTICGT-2012-RensinkZ #abstraction
Pattern-Based Graph Abstraction (AR, EZ), pp. 66–80.
ICGTICGT-2012-TaentzerML #co-evolution
Co-transformation of Graphs and Type Graphs with Application to Model Co-evolution (GT, FM, YL), pp. 326–340.
CHICHI-2012-ZiemkiewiczGL #analysis #visualisation
Analysis within and between graphs: observed user strategies in immunobiology visualization (CZ, SRG, DHL), pp. 1655–1658.
CSCWCSCW-2012-LungE #collaboration #named #reasoning
Inflo: collaborative reasoning via open calculation graphs (JL, SME), pp. 1199–1202.
ICEISICEIS-v2-2012-ChenFZ #3d #visualisation #web
Exploring Structural Properties of Web Graphs through 3D Visualization (ZC, AF, KZ), pp. 233–238.
CIKMCIKM-2012-BodenGS #clustering #evolution
Tracing clusters in evolving graphs with node attributes (BB, SG, TS), pp. 2331–2334.
CIKMCIKM-2012-CaoYDWW #modelling #process #recommendation #workflow
Graph-based workflow recommendation: on improving business process modeling (BC, JY, SD, DW, ZW), pp. 1527–1531.
CIKMCIKM-2012-CreceliusS #maintenance #nearest neighbour #scalability
Pay-as-you-go maintenance of precomputed nearest neighbors in large graphs (TC, RS), pp. 952–961.
CIKMCIKM-2012-DuanWZS #classification #twitter
Graph-based collective classification for tweets (YD, FW, MZ, HYS), pp. 2323–2326.
CIKMCIKM-2012-DurakPKS #modelling #network
Degree relations of triangles in real-world networks and graph models (ND, AP, TGK, CS), pp. 1712–1716.
CIKMCIKM-2012-EldardiryN #analysis #classification #how #predict
An analysis of how ensembles of collective classifiers improve predictions in graphs (HE, JN), pp. 225–234.
CIKMCIKM-2012-EmrichKNRSZ #monte carlo #nondeterminism #probability #query
Exploration of monte-carlo based probabilistic query processing in uncertain graphs (TE, HPK, JN, MR, AS, AZ), pp. 2728–2730.
CIKMCIKM-2012-GaoCK #keyword #scalability
Information-complete and redundancy-free keyword search over large data graphs (BJG, ZC, QK), pp. 2639–2642.
CIKMCIKM-2012-Gomez-RodriguezR #online #social
Bridging offline and online social graph dynamics (MGR, MR), pp. 2447–2450.
CIKMCIKM-2012-GubichevN #approximate #performance #scalability
Fast approximation of steiner trees in large graphs (AG, TN), pp. 1497–1501.
CIKMCIKM-2012-KimCS
Impact neighborhood indexing (INI) in diffusion graphs (JHK, KSC, MLS), pp. 2184–2188.
CIKMCIKM-2012-LeePKL #named #novel #ranking #recommendation
PathRank: a novel node ranking measure on a heterogeneous graph for recommender systems (SL, SP, MK, SgL), pp. 1637–1641.
CIKMCIKM-2012-LiuCBLR #mining
Utilizing common substructures to speedup tensor factorization for mining dynamic graphs (WL, JC, JB, CL, KR), pp. 435–444.
CIKMCIKM-2012-LiuKCBLPR #on the
On compressing weighted time-evolving graphs (WL, AK, JC, JB, CL, JP, KR), pp. 2319–2322.
CIKMCIKM-2012-LiYWK #proximity #scalability
Density index and proximity search in large graphs (NL, XY, ZW, AK), pp. 235–244.
CIKMCIKM-2012-LuYW #framework #image #named #novel #social
SRGSIS: a novel framework based on social relationship graph for social image search (BL, YY, GW), pp. 2615–2618.
CIKMCIKM-2012-MeleBG #recommendation
The early-adopter graph and its application to web-page recommendation (IM, FB, AG), pp. 1682–1686.
CIKMCIKM-2012-MendesMZB #similarity #using
Measuring website similarity using an entity-aware click graph (PNM, PM, HZ, RB), pp. 1697–1701.
CIKMCIKM-2012-PanZ #correlation #data type #named #query
CGStream: continuous correlated graph query for data streams (SP, XZ), pp. 1183–1192.
CIKMCIKM-2012-PanZ12a #query
Continuous top-k query for graph streams (SP, XZ), pp. 2659–2662.
CIKMCIKM-2012-RahmanBH #algorithm #analysis #approximate #named #scalability
GRAFT: an approximate graphlet counting algorithm for large graph analysis (MR, MB, MAH), pp. 1467–1471.
CIKMCIKM-2012-RamachandranG #identification #representation
A word-order based graph representation for relevance identification (LR, EFG), pp. 2327–2330.
CIKMCIKM-2012-SakrEH #hybrid #named #query #scalability
G-SPARQL: a hybrid engine for querying large attributed graphs (SS, SE, YH), pp. 335–344.
CIKMCIKM-2012-ShenWLW #approach #ontology
A graph-based approach for ontology population with named entities (WS, JW, PL, MW), pp. 345–354.
CIKMCIKM-2012-TongPEFF #scalability
Gelling, and melting, large graphs by edge manipulation (HT, BAP, TER, MF, CF), pp. 245–254.
CIKMCIKM-2012-WangWLL #keyword #ranking #using #wiki
Exploring simultaneous keyword and key sentence extraction: improve graph-based ranking using wikipedia (XW, LW, JL, SL), pp. 2619–2622.
CIKMCIKM-2012-WeningerBH #documentation #topic
Document-topic hierarchies from document graphs (TW, YB, JH), pp. 635–644.
CIKMCIKM-2012-YangYGL #multi
Finding the optimal path over multi-cost graphs (YY, JXY, HG, JL), pp. 2124–2128.
CIKMCIKM-2012-ZhukovskiyVPOGGSR #empirical #validation #web
Empirical validation of the buckley-osthus model for the web host graph: degree and edge distributions (MZ, DV, YP, LO, EG, GG, PS, AMR), pp. 1577–1581.
CIKMCIKM-2012-ZhuYCQ #approach #classification #feature model
Graph classification: a diversified discriminative feature selection approach (YZ, JXY, HC, LQ), pp. 205–214.
ECIRECIR-2012-Bloom #analysis
Applying Power Graph Analysis to Weighted Graphs (NB), pp. 548–551.
ICMLICML-2012-AlamgirL #distance #nearest neighbour #random
Shortest path distance in random k-nearest neighbor graphs (MA, UvL), p. 163.
ICMLICML-2012-BorboudakisT #constraints #information management #network
Incorporating Causal Prior Knowledge as Path-Constraints in Bayesian Networks and Maximal Ancestral Graphs (GB, IT), p. 59.
ICMLICML-2012-Busa-FeketeBK #classification #performance #using
Fast classification using sparse decision DAGs (RBF, DB, BK), p. 99.
ICMLICML-2012-HaiderS #clustering #using
Finding Botnets Using Minimal Graph Clusterings (PH, TS), p. 37.
ICMLICML-2012-JalaliS #dependence #learning
Learning the Dependence Graph of Time Series with Latent Factors (AJ, SS), p. 83.
ICMLICML-2012-KimL #multi
Latent Multi-group Membership Graph Model (MK, JL), p. 124.
ICMLICML-2012-KriegeM #kernel
Subgraph Matching Kernels for Attributed Graphs (NK, PM), p. 42.
ICMLICML-2012-QuadriantoCL #clique #persistent #set
The Most Persistent Soft-Clique in a Set of Sampled Graphs (NQ, CC, CHL), p. 32.
ICPRICPR-2012-AlbarelliBRVT #higher-order #recognition #representation
A stable graph-based representation for object recognition through high-order matching (AA, FB, LR, SV, AT), pp. 3341–3344.
ICPRICPR-2012-BaiHHR #clustering #complexity #using
Graph clustering using graph entropy complexity traces (LB, ERH, LH, PR), pp. 2881–2884.
ICPRICPR-2012-BaiHR #kernel #using
Jensen-Shannon graph kernel using information functionals (LB, ERH, PR), pp. 2877–2880.
ICPRICPR-2012-BarducciM #component #recognition
Object recognition in floor plans by graphs of white connected components (AB, SM), pp. 298–301.
ICPRICPR-2012-ChenWY #clustering #dataset
Centroid-based clustering for graph datasets (LC, SW, XY), pp. 2144–2147.
ICPRICPR-2012-ChowdhuryKPD #design #using #video
Video storyboard design using Delaunay graphs (ASC, SKK, RP, MND), pp. 3108–3111.
ICPRICPR-2012-DuttaGLBP #documentation #kernel #random #visual notation
Combination of product graph and random walk kernel for symbol spotting in graphical documents (AD, JG, JL, HB, UP), pp. 1663–1666.
ICPRICPR-2012-GaoTLW #re-engineering
A graph-based method of newspaper article reconstruction (LG, ZT, XL, YW), pp. 1566–1569.
ICPRICPR-2012-GauzereBVB #kernel
Graph kernels based on relevant patterns and cycle information for chemoinformatics (BG, LB, DV, MB), pp. 1775–1778.
ICPRICPR-2012-GhoseMOMLFVCSM12a #3d #energy #framework #learning #probability #segmentation
Graph cut energy minimization in a probabilistic learning framework for 3D prostate segmentation in MRI (SG, JM, AO, RM, XL, JF, JCV, JC, DS, FM), pp. 125–128.
ICPRICPR-2012-HanWHBR #generative #probability
Sampling graphs from a probabilistic generative model (LH, RCW, ERH, LB, PR), pp. 1643–1646.
ICPRICPR-2012-HidoK #learning #similarity
Hash-based structural similarity for semi-supervised Learning on attribute graphs (SH, HK), pp. 3009–3012.
ICPRICPR-2012-ItohTA #3d #image #sequence #using
3D tracking of soccer players using time-situation graph in monocular image sequence (HI, TT, YA), pp. 2532–2536.
ICPRICPR-2012-LiuLLC #image #reduction
Graph-based dimensionality reduction for KNN-based image annotation (XL, RL, FL, QC), pp. 1253–1256.
ICPRICPR-2012-LiuSZ #feature model
Sparsity Score: A new filter feature selection method based on graph (ML, DS, DZ), pp. 959–962.
ICPRICPR-2012-NarayanamN #algorithm #community #detection #distributed #game studies #information management #social
A game theory inspired, decentralized, local information based algorithm for community detection in social graphs (RN, YN), pp. 1072–1075.
ICPRICPR-2012-PourdamghaniRZ #estimation #learning #metric
Metric learning for graph based semi-supervised human pose estimation (NP, HRR, MZ), pp. 3386–3389.
ICPRICPR-2012-RebagliatiSPS #distance #edit distance #set #using
Computing the graph edit distance using dominant sets (NR, ASR, MP, FS), pp. 1080–1083.
ICPRICPR-2012-RubioSLP #higher-order #image #representation
Image contextual representation and matching through hierarchies and higher order graphs (JCR, JS, AML, NP), pp. 2664–2667.
ICPRICPR-2012-SerratosaCS #interactive
Interactive graph matching by means of imposing the pairwise costs (FS, XC, ASR), pp. 1298–1301.
ICPRICPR-2012-ShenMZ #analysis #learning #online
Unsupervised online learning trajectory analysis based on weighted directed graph (YS, ZM, JZ), pp. 1306–1309.
ICPRICPR-2012-ValevY #classification #clustering #using
Classification using graph partitioning (VV, NY), pp. 1261–1264.
ICPRICPR-2012-WahlbergB #segmentation
Graph based line segmentation on cluttered handwritten manuscripts (FW, AB), pp. 1570–1573.
ICPRICPR-2012-WangAG #adaptation #feature model #matrix
Adaptive graph regularized Nonnegative Matrix Factorization via feature selection (JW, IA, XG), pp. 963–966.
ICPRICPR-2012-WeibelDWR #detection #using
Contrast-enhancing seam detection and blending using graph cuts (TW, CD, DW, RR), pp. 2732–2735.
ICPRICPR-2012-WongLTYCCBW #approach #automation #locality
Automatic localization of the macula in a supervised graph-based approach with contextual superpixel features (DWKW, JL, NMT, FY, XC, CMGC, MB, TYW), pp. 2063–2066.
ICPRICPR-2012-YiP #classification
Sparse Granger causality graphs for human action classification (SY, VP), pp. 3374–3377.
ICPRICPR-2012-ZhangCYLS #constraints
Stereo matching with Global Edge Constraint and Graph Cuts (HZ, FC, DY, YL, MS), pp. 372–375.
ICPRICPR-2012-ZhaoZWL #detection #mobile #robust
Robust mobile spamming detection via graph patterns (YZ, ZZ, YW, JL), pp. 983–986.
KDDKDD-2012-BahmaniKMU #evolution #rank
PageRank on an evolving graph (BB, RK, MM, EU), pp. 24–32.
KDDKDD-2012-BodenGHS #mining #multi
Mining coherent subgraphs in multi-layer graphs with edge labels (BB, SG, HH, TS), pp. 1258–1266.
KDDKDD-2012-ChanLLBR #mining #multi #named
SeqiBloc: mining multi-time spanning blockmodels in dynamic graphs (JC, WL, CL, JB, KR), pp. 651–659.
KDDKDD-2012-ChauAVTF #interactive #named #scalability #visualisation
TourViz: interactive visualization of connection pathways in large graphs (DHC, LA, JV, HT, CF), pp. 1516–1519.
KDDKDD-2012-CorreaL #clustering #using
Locally-scaled spectral clustering using empty region graphs (CDC, PL), pp. 1330–1338.
KDDKDD-2012-FengHKBP #mining
Summarization-based mining bipartite graphs (JF, XH, BK, CB, CP), pp. 1249–1257.
KDDKDD-2012-GiatsidisBTV #collaboration #network #visual notation
Visual exploration of collaboration networks based on graph degeneracy (CG, KB, DMT, MV), pp. 1512–1515.
KDDKDD-2012-HendersonGETBAKFL #mining #named #scalability
RolX: structural role extraction & mining in large graphs (KH, BG, TER, HT, SB, LA, DK, CF, LL), pp. 1231–1239.
KDDKDD-2012-Li12b #algorithm #mining #nondeterminism
Algorithms for mining uncertain graph data (JL), p. 813.
KDDKDD-2012-SeelandKK #clustering #kernel #learning
A structural cluster kernel for learning on graphs (MS, AK, SK), pp. 516–524.
KDDKDD-2012-SondhiSTZ #framework #mining #named
SympGraph: a framework for mining clinical notes through symptom relation graphs (PS, JS, HT, CZ), pp. 1167–1175.
KDDKDD-2012-StantonK #clustering #distributed #scalability #streaming
Streaming graph partitioning for large distributed graphs (IS, GK), pp. 1222–1230.
KDDKDD-2012-YangYLSWY
Feature grouping and selection over an undirected graph (SY, LY, YCL, XS, PW, JY), pp. 922–930.
RecSysRecSys-2012-BelloginP #clustering #collaboration #using
Using graph partitioning techniques for neighbour selection in user-based collaborative filtering (AB, JP), pp. 213–216.
RecSysRecSys-2012-Heitmann #framework #multi #personalisation #semantics
An open framework for multi-source, cross-domain personalisation with semantic interest graphs (BH), pp. 313–316.
SEKESEKE-2012-QiXW #concurrent #interprocedural #reachability #slicing #source code
Slicing Concurrent Interprocedural Programs Based on Program Reachability Graphs (XQ, XX, PW), pp. 293–298.
SEKESEKE-2012-ZhangLS #impact analysis #mining
Mining Call Graph for Change Impact Analysis (QZ, BL, XS), pp. 7–12.
SIGIRSIGIR-2012-FangHC
Confidence-aware graph regularization with heterogeneous pairwise features (YF, BJPH, KCCC), pp. 951–960.
SIGIRSIGIR-2012-GaoWL #information retrieval #learning #mining #scalability
Large-scale graph mining and learning for information retrieval (BG, TW, TYL), pp. 1194–1195.
SIGIRSIGIR-2012-KahngL #rdf
Exploiting paths for entity search in RDF graphs (MK, SgL), pp. 1027–1028.
SIGIRSIGIR-2012-YangLLR #analysis #twitter
Finding interesting posts in Twitter based on retweet graph analysis (MCY, JTL, SWL, HCR), pp. 1073–1074.
ECOOPECOOP-2012-AliL
Application-Only Call Graph Construction (KA, OL), pp. 688–712.
OOPSLAOOPSLA-2012-PrountzosMP #concurrent #named #source code
Elixir: a system for synthesizing concurrent graph programs (DP, RM, KP), pp. 375–394.
LOPSTRLOPSTR-2012-GieslSSEF #evaluation #logic programming #source code #symbolic computation #term rewriting
Symbolic Evaluation Graphs and Term Rewriting — A General Methodology for Analyzing Logic Programs (JG, TS, PSK, FE, CF), p. 1.
PADLPADL-2012-Lesniak #algorithm #haskell #named
Palovca: Describing and Executing Graph Algorithms in Haskell (ML), pp. 153–167.
PPDPPPDP-2012-GieslSSEF #evaluation #logic programming #source code #symbolic computation #term rewriting
Symbolic evaluation graphs and term rewriting: a general methodology for analyzing logic programs (JG, TS, PSK, FE, CF), pp. 1–12.
ICSEICSE-2012-BhattacharyaINF #analysis #evolution #predict
Graph-based analysis and prediction for software evolution (PB, MI, IN, MF), pp. 419–429.
ICSEICSE-2012-NguyenNNN12a #code completion #named
GraPacc: A graph-based pattern-oriented, context-sensitive code completion tool (ATN, HAN, TTN, TNN), pp. 1407–1410.
ICSEICSE-2012-NguyenNNTNAN #code completion #source code
Graph-based pattern-oriented, context-sensitive source code completion (ATN, TTN, HAN, AT, HVN, JMAK, TNN), pp. 69–79.
SACSAC-2012-BenreguiaK #consistency #morphism #problem
A consistency rule for graph isomorphism problem (BB, HK), pp. 906–911.
SACSAC-2012-BrandnerC #data flow #dependence
Copy elimination on data dependence graphs (FB, QC), pp. 1916–1918.
SACSAC-2012-DragoB #analysis #architecture #design #manycore #named
DAG3: a tool for design and analysis of applications for multicore architectures (MLD, JB), pp. 1159–1164.
SACSAC-2012-KokaANSY #grid
Row manipulation in the heterogeneous tabular forms with a hexadecimal grid graph model (SK, KA, KN, YS, TY), pp. 792–793.
SACSAC-2012-NagarAB #functional #similarity #using
Computing gene functional similarity using combined graphs (AN, HAM, SB), pp. 1381–1386.
SACSAC-2012-PerroneDH #model checking
A model checker for Bigraphs (GP, SD, TTH), pp. 1320–1325.
SACSAC-2012-PriamiQZ #biology #imperative #self
An imperative language of self-modifying graphs for biological systems (CP, PQ, RZ), pp. 1903–1909.
SACSAC-2012-VirgilioR #approximate #biology #rdf
Approximate matching over biological RDF graphs (RDV, SER), pp. 1413–1414.
ASPLOSASPLOS-2012-HongCSO #analysis #domain-specific language #named #performance
Green-Marl: a DSL for easy and efficient graph analysis (SH, HC, ES, KO), pp. 349–362.
CGOCGO-2012-ParkCA #modelling #predict #using
Using graph-based program characterization for predictive modeling (EP, JC, MAA), pp. 196–206.
DACDAC-2012-ChoiOKH #architecture #data flow #manycore
Executing synchronous dataflow graphs on a SPM-based multicore architecture (JC, HO, SK, SH), pp. 664–671.
DATEDATE-2012-DamavandpeymaSBGC #data flow #modelling
Modeling static-order schedules in synchronous dataflow graphs (MD, SS, TB, MG, HC), pp. 775–780.
DATEDATE-2012-LiuTW #analysis #approach #parallel #statistics
Parallel statistical analysis of analog circuits by GPU-accelerated graph-based approach (XL, SXDT, HW), pp. 852–857.
DATEDATE-2012-MeissnerMLH #framework #morphism #performance #synthesis #testing
Fast isomorphism testing for a graph-based analog circuit synthesis framework (MM, OM, LL, LH), pp. 757–762.
DATEDATE-2012-ThieleE #analysis #data flow #optimisation #performance
Optimizing performance analysis for synchronous dataflow graphs with shared resources (DT, RE), pp. 635–640.
DATEDATE-2012-YangGBSC #game studies #policy #resource management
Playing games with scenario- and resource-aware SDF graphs through policy iteration (YY, MG, TB, SS, HC), pp. 194–199.
HPDCHPDC-2012-UenoS #benchmark #metric #scalability
Highly scalable graph search for the Graph500 benchmark (KU, TS), pp. 149–160.
ISMMISMM-2012-Nasre #analysis #constraints #performance #points-to
Exploiting the structure of the constraint graph for efficient points-to analysis (RN), pp. 121–132.
OSDIOSDI-2012-GonzalezLGBG #distributed #named
PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs (JEG, YL, HG, DB, CG), pp. 17–30.
OSDIOSDI-2012-KyrolaBG #named #scalability
GraphChi: Large-Scale Graph Computation on Just a PC (AK, GEB, CG), pp. 31–46.
PPoPPPPoPP-2012-MerrillGG #gpu #scalability #traversal
Scalable GPU graph traversal (DM, MG, ASG), pp. 117–128.
PPoPPPPoPP-2012-ZhongH #overview
An overview of Medusa: simplified graph processing on GPUs (JZ, BH), pp. 283–284.
FASEFASE-2012-MolRH #java
Graph Transforming Java Data (MdM, AR, JJH), pp. 209–223.
FASEFASE-2012-SilvaTT #dependence #erlang
System Dependence Graphs in Sequential Erlang (JS, ST, CT), pp. 486–500.
STOCSTOC-2012-AbrahamCG #approximate #distance
Fully dynamic approximate distance oracles for planar graphs via forbidden-set distance labels (IA, SC, CG), pp. 1199–1218.
STOCSTOC-2012-AlonMS #scalability
Nearly complete graphs decomposable into large induced matchings and their applications (NA, AM, BS), pp. 1079–1090.
STOCSTOC-2012-Chuzhoy12a #constant
Routing in undirected graphs with constant congestion (JC), pp. 855–874.
STOCSTOC-2012-GroheM #morphism #theorem
Structure theorem and isomorphism test for graphs with excluded topological subgraphs (MG, DM), pp. 173–192.
STOCSTOC-2012-KaufmanL #symmetry #transitive
Edge transitive ramanujan graphs and symmetric LDPC good codes (TK, AL), pp. 359–366.
STOCSTOC-2012-Molloy #random
The freezing threshold for k-colourings of a random graph (MM), pp. 921–930.
CSLCSL-2012-KotekM #matrix #parametricity
Connection Matrices and the Definability of Graph Parameters (TK, JAM), pp. 411–425.
CSLCSL-2012-Makowsky #complexity #parametricity
Definability and Complexity of Graph Parameters (JAM), pp. 14–15.
ICSTICST-2012-DengJ #dependence
Weighted System Dependence Graph (FD, JAJ), pp. 380–389.
ICSTICST-2012-MalikK #analysis #using
Dynamic Shape Analysis Using Spectral Graph Properties (MZM, SK), pp. 211–220.
LICSLICS-2012-BarceloFL #logic #problem
Graph Logics with Rational Relations and the Generalized Intersection Problem (PB, DF, LL), pp. 115–124.
ICDARICDAR-2011-DuttaLP
Symbol Spotting in Line Drawings through Graph Paths Hashing (AD, JL, UP), pp. 982–986.
ICDARICDAR-2011-LiuLS #image #retrieval #using
Retrieval of Envelope Images Using Graph Matching (LL, YL, CYS), pp. 99–103.
ICDARICDAR-2011-LuqmanRLB #documentation #image
Subgraph Spotting through Explicit Graph Embedding: An Application to Content Spotting in Graphic Document Images (MML, JYR, JL, TB), pp. 870–874.
ICDARICDAR-2011-ManoharVCPN #clustering #segmentation
Graph Clustering-Based Ensemble Method for Handwritten Text Line Segmentation (VM, SNPV, HC, RP, PN), pp. 574–578.
ICDARICDAR-2011-Saund #approach #image #maintenance
A Graph Lattice Approach to Maintaining Dense Collections of Subgraphs as Image Features (ES), pp. 1069–1074.
ICDARICDAR-2011-WangWZ #online #using #verification
On-line Signature Verification Using Segment-to-Segment Graph Matching (KW, YW, ZZ), pp. 804–808.
PODSPODS-2011-BarceloLR #query
Querying graph patterns (PB, LL, JLR), pp. 199–210.
SIGMODSIGMOD-2011-FanLLTWW #incremental #pattern matching
Incremental graph pattern matching (WF, JL, JL, ZT, XW, YW), pp. 925–936.
SIGMODSIGMOD-2011-GuanWZSY #correlation #ranking
Assessing and ranking structural correlations in graphs (ZG, JW, QZ, AKS, XY), pp. 937–948.
SIGMODSIGMOD-2011-HanPLKY #analysis #performance
iGraph in action: performance analysis of disk-based graph indexing techniques (WSH, MDP, JL, RK, JXY), pp. 1241–1242.
SIGMODSIGMOD-2011-KhanLYGCT #network #performance #scalability
Neighborhood based fast graph search in large networks (AK, NL, XY, ZG, SC, ST), pp. 901–912.
SIGMODSIGMOD-2011-KonstantinidisA #approach #query #scalability
Scalable query rewriting: a graph-based approach (GK, JLA), pp. 97–108.
SIGMODSIGMOD-2011-LianC #performance #probability #query #rdf
Efficient query answering in probabilistic RDF graphs (XL, LC), pp. 157–168.
SIGMODSIGMOD-2011-SatuluriPR #clustering #scalability
Local graph sparsification for scalable clustering (VS, SP, YR), pp. 721–732.
SIGMODSIGMOD-2011-ZhaoLXH #multi #network
Graph cube: on warehousing and OLAP multidimensional networks (PZ, XL, DX, JH), pp. 853–864.
TPDLTPDL-2011-TsatsaronisVTRNSZ #how #mining #modelling
How to Become a Group Leader? or Modeling Author Types Based on Graph Mining (GT, IV, ST, MR, KN, MS, MZ), pp. 15–26.
VLDBVLDB-2011-BlausteinCSAR
Surrogate Parenthood: Protected and Informative Graphs (BTB, AC, LS, MDA, AR), pp. 518–527.
VLDBVLDB-2011-Cudre-MaurouxE #data transformation
Graph Data Management Systems for New Application Domains (PCM, SE), pp. 1510–1511.
VLDBVLDB-2011-HuangAR #query #rdf #scalability
Scalable SPARQL Querying of Large RDF Graphs (JH, DJA, KR), pp. 1123–1134.
VLDBVLDB-2011-JinLDW #constraints #nondeterminism #reachability
Distance-Constraint Reachability Computation in Uncertain Graphs (RJ, LL, BD, HW), pp. 551–562.
VLDBVLDB-2011-KargarA #clique #keyword
Keyword Search in Graphs: Finding r-cliques (MK, AA), pp. 681–692.
VLDBVLDB-2011-KarwaRSY #analysis
Private Analysis of Graph Structure (VK, SR, AS, GY), pp. 1146–1157.
VLDBVLDB-2011-ParameswaranSGPW
Human-assisted graph search: it’s okay to ask questions (AGP, ADS, HGM, NP, JW), pp. 267–278.
VLDBVLDB-2011-RenLKZC #evolution #on the #query #sequence
On Querying Historical Evolving Graph Sequences (CR, EL, BK, XZ, RC), pp. 726–737.
VLDBVLDB-2011-YangPS #mining #multi #performance
Fast Sparse Matrix-Vector Multiplication on GPUs: Implications for Graph Mining (XY, SP, PS), pp. 231–242.
VLDBVLDB-2011-YangPS11a #database #relational #summary
Summary Graphs for Relational Database Schemas (XY, CMP, DS), pp. 899–910.
VLDBVLDB-2011-YuanWWC #nondeterminism #performance #scalability
Efficient Subgraph Search over Large Uncertain Graphs (YY, GW, HW, LC), pp. 876–886.
VLDBVLDB-2012-GaoJZYJW11 #approach #relational #scalability
Relational Approach for Shortest Path Discovery over Large Graphs (JG, RJ, JZ, JXY, XJ, TW), pp. 358–369.
VLDBVLDB-2012-MaCFHW11 #pattern matching
Capturing Topology in Graph Pattern Matching (SM, YC, WF, JH, TW), pp. 310–321.
VLDBVLDB-2012-ZhaoAW11 #estimation #named #query #sketching
gSketch: On Query Estimation in Graph Streams (PZ, CCA, MW), pp. 193–204.
ICSMEICSM-2011-PaymalPBS #evolution #metric #process #using
Measuring disruption from software evolution activities using graph-based metrics (PP, RP, SB, HPS), pp. 532–535.
ICSMEICSM-2011-SunKZ #api #detection #library
Graph-based detection of library API imitations (CS, SCK, SJZ), pp. 183–192.
SCAMSCAM-2011-PavluSK #alias #analysis #comparison #precise #set
Computation of Alias Sets from Shape Graphs for Comparison of Shape Analysis Precision (VP, MS, AK), pp. 25–34.
SCAMSCAM-2011-SawinR #algorithm
Assumption Hierarchy for a CHA Call Graph Construction Algorithm (JS, AR), pp. 35–44.
WCREWCRE-2011-WangLJ #code search #dependence #topic
Code Search via Topic-Enriched Dependence Graph Matching (SW, DL, LJ), pp. 119–123.
DLTDLT-J-2010-YuanCL11 #fault
Linearly Many Faults in (n, k)-Star Graphs (AY, EC, LL), pp. 1729–1745.
AFLAFL-2011-LoeligerN #design #user interface
Affordance Graphs for User Interface Design: Application of Category-theoretic Constructs (EAL, CLN), pp. 392–394.
DLTDLT-2011-KitaevSSU #on the
On the Representability of Line Graphs (SK, PS, CS, ), pp. 478–479.
ICALPICALP-v1-2011-AdlerKKLST #bound
Tight Bounds for Linkages in Planar Graphs (IA, SGK, PKK, DL, SS, DMT), pp. 110–121.
ICALPICALP-v1-2011-BordewichK #agile #bound #set
Rapid Mixing of Subset Glauber Dynamics on Graphs of Bounded Tree-Width (MB, RJK), pp. 533–544.
ICALPICALP-v1-2011-ChengMS
Center Stable Matchings and Centers of Cover Graphs of Distributive Lattices (CTC, EM, IS), pp. 678–689.
ICALPICALP-v1-2011-FarzanK #distance #navigation
Compact Navigation and Distance Oracles for Graphs with Small Treewidth (AF, SK), pp. 268–280.
ICALPICALP-v1-2011-KawarabayashiKS #approximate #bound #distance
Linear-Space Approximate Distance Oracles for Planar, Bounded-Genus and Minor-Free Graphs (KiK, PNK, CS), pp. 135–146.
ICALPICALP-v1-2011-KuhnM
Vertex Cover in Graphs with Locally Few Colors (FK, MM), pp. 498–509.
ICALPICALP-v1-2011-Moldenhauer #algorithm #approximate
Primal-Dual Approximation Algorithms for Node-Weighted Steiner Forest on Planar Graphs (CM), pp. 748–759.
ICALPICALP-v1-2011-Nonner #clique #clustering
Clique Clustering Yields a PTAS for max-Coloring Interval Graphs (TN), pp. 183–194.
ICALPICALP-v2-2011-Chechik #fault tolerance
Fault-Tolerant Compact Routing Schemes for General Graphs (SC), pp. 101–112.
ICALPICALP-v2-2011-HermelinLWY #distance
Distance Oracles for Vertex-Labeled Graphs (DH, AL, OW, RY), pp. 490–501.
ICALPICALP-v2-2011-MegowMS #algorithm #online
Online Graph Exploration: New Results on Old and New Algorithms (NM, KM, PS), pp. 478–489.
RTARTA-2011-GrathwohlKPS #named #reduction #term rewriting #visualisation #λ-calculus
Anagopos: A Reduction Graph Visualizer for Term Rewriting and λ Calculus (NBBG, JK, JDP, JGS), pp. 61–70.
GCMGCM-2010-HoffmannM11 #adaptation #diagrams #generative
Generating Instance Graphs from Class Diagrams with Adaptive Star Grammars (BH, MM).
GCMGCM-2010-PicardM11 #embedded #induction #problem #representation
Coinductive Graph Representation: the Problem of Embedded Lists (CP, RM).
GCMGCM-2010-PlumpSS11 #automaton #finite #source code
Minimizing Finite Automata with Graph Programs (DP, RS, AS).
AGTIVEAGTIVE-2011-GalvaoZRWA #analysis #knowledge-based
Knowledge-Based Graph Exploration Analysis (IG, EZ, AR, LW, MA), pp. 105–120.
GT-VMTGT-VMT-2011-BrugginkH #decidability
Decidability and Expressiveness of Finitely Representable Recognizable Graph Languages (HJSB, MH).
GT-VMTGT-VMT-2011-VandinL #maude #model checking #towards
Towards a Maude Tool for Model Checking Temporal Graph Properties (AV, ALL).
CHICHI-2011-GuyPDGT #crowdsourcing #game studies #social
Guess who?: enriching the social graph through a crowdsourcing game (IG, AP, TD, OG, IT), pp. 1373–1382.
HCIHCD-2011-NazemiBK #taxonomy #visual notation #visualisation
User-Oriented Graph Visualization Taxonomy: A Data-Oriented Examination of Visual Features (KN, MB, AK), pp. 576–585.
HCIHCI-DDA-2011-HeL #image #modelling #segmentation
An Image Segmentation Method for Chinese Paintings by Combining Deformable Models with Graph Cuts (NH, KL), pp. 571–579.
HCIHCI-ITE-2011-AbushamB #recognition #using
Face Recognition Using Local Graph Structure (LGS) (EEAA, HKB), pp. 169–175.
VISSOFTVISSOFT-2011-ErdemirTB #named #object-oriented #quality #visualisation
E-Quality: A graph based object oriented software quality visualization tool (UE, UT, FB), pp. 1–8.
VISSOFTVISSOFT-2011-LonnbergBM #concurrent #dependence #source code #visualisation
Visualising concurrent programs with dynamic dependence graphs (JL, MBA, LM), pp. 1–4.
CAiSECAiSE-2011-GuabtniNB #correlation #interactive #using
Using Graph Aggregation for Service Interaction Message Correlation (AG, HRMN, BB), pp. 642–656.
EDOCEDOC-2011-HildebrandtMS #design #using
Designing a Cross-Organizational Case Management System Using Dynamic Condition Response Graphs (TTH, RRM, TS), pp. 161–170.
CIKMCIKM-2011-CaoCS #named
Skynets: searching for minimum trees in graphs with incomparable edge weights (HC, KSC, MLS), pp. 1775–1784.
CIKMCIKM-2011-ClaudeL #social #web
Practical representations for web and social graphs (FC, SL), pp. 1185–1190.
CIKMCIKM-2011-DavisLMR #detection
Detecting anomalies in graphs with numeric labels (MD, WL, PCM, GR), pp. 1197–1202.
CIKMCIKM-2011-DengLPCX #ad hoc #database #predict #query #reachability
Predicting the optimal ad-hoc index for reachability queries on graph databases (JD, FL, YP, BC, JX), pp. 2357–2360.
CIKMCIKM-2011-ElbassuoniB #keyword #rdf
Keyword search over RDF graphs (SE, RB), pp. 237–242.
CIKMCIKM-2011-KermarrecLT #distributed #social
Distributed social graph embedding (AMK, VL, GT), pp. 1209–1214.
CIKMCIKM-2011-KimJHSZ #approach #corpus #mining
Mining entity translations from comparable corpora: a holistic graph mapping approach (JK, LJ, SwH, YIS, MZ), pp. 1295–1304.
CIKMCIKM-2011-MalikMOSS #ecosystem
Exploring the corporate ecosystem with a semi-supervised entity graph (HHM, IM, MOO, SS, SS), pp. 1857–1866.
CIKMCIKM-2011-NiuLX #named #ranking #using
DIGRank: using global degree to facilitate ranking in an incomplete graph (XN, LL, KX), pp. 2297–2300.
CIKMCIKM-2011-ShiLY #predict
Collective prediction with latent graphs (XS, YL, PSY), pp. 1127–1136.
CIKMCIKM-2011-TretyakovAGVD #estimation #performance #scalability
Fast fully dynamic landmark-based estimation of shortest path distances in very large graphs (KT, AAC, LGB, JV, MD), pp. 1785–1794.
CIKMCIKM-2011-WangNSTC #clustering #dependence #documentation #representation
Representing document as dependency graph for document clustering (YW, XN, JTS, YT, ZC), pp. 2177–2180.
CIKMCIKM-2011-WangWLZZ #analysis #approach #classification #hashtag #sentiment #topic #twitter
Topic sentiment analysis in twitter: a graph-based hashtag sentiment classification approach (XW, FW, XL, MZ, MZ), pp. 1031–1040.
CIKMCIKM-2011-XieY #named #performance #scalability
CP-index: on the efficient indexing of large graphs (YX, PSY), pp. 1795–1804.
CIKMCIKM-2011-XuZYCXZ #constraints #reachability #scalability
Answering label-constraint reachability in large graphs (KX, LZ, JXY, LC, YX, DZ), pp. 1595–1600.
CIKMCIKM-2011-YangZJ #multi #named #query
DELTA: indexing and querying multi-labeled graphs (JY, SZ, WJ), pp. 1765–1774.
CIKMCIKM-2011-ZhouPW #constraints #keyword #performance #scalability
Efficient association discovery with keyword-based constraints on large graph data (MZ, YP, YW), pp. 2441–2444.
CIKMCIKM-2011-ZhuQYKL #performance #quality #scalability
High efficiency and quality: large graphs matching (YZ, LQ, JXY, YK, XL), pp. 1755–1764.
ICMLICML-2011-JalaliCSX #clustering #optimisation
Clustering Partially Observed Graphs via Convex Optimization (AJ, YC, SS, HX), pp. 1001–1008.
ICMLICML-2011-LiuWKC
Hashing with Graphs (WL, JW, SK, SFC), pp. 1–8.
ICMLICML-2011-LuoDNH
Cauchy Graph Embedding (DL, CHQD, FN, HH), pp. 553–560.
ICMLICML-2011-WickRBCM #named
SampleRank: Training Factor Graphs with Atomic Gradients (MLW, KR, KB, AC, AM), pp. 777–784.
KDDKDD-2011-AoyamaSSU #approximate #performance #similarity
Fast approximate similarity search based on degree-reduced neighborhood graphs (KA, KS, HS, NU), pp. 1055–1063.
KDDKDD-2011-BifetHPG #data type #evolution #mining
Mining frequent closed graphs on evolving data streams (AB, GH, BP, RG), pp. 591–599.
KDDKDD-2011-ChauKHF #interactive #machine learning #named #scalability #visualisation
Apolo: interactive large graph sensemaking by combining machine learning and visualization (DHC, AK, JIH, CF), pp. 739–742.
KDDKDD-2011-DubeyCB #ranking
Diversity in ranking via resistive graph centers (AD, SC, CB), pp. 78–86.
KDDKDD-2011-GaoLWWL #metadata #ranking #scalability
Semi-supervised ranking on very large graphs with rich metadata (BG, TYL, WW, TW, HL), pp. 96–104.
KDDKDD-2011-HendersonGLAETF #mining #recursion #using
It’s who you know: graph mining using recursive structural features (KH, BG, LL, LA, TER, HT, CF), pp. 663–671.
KDDKDD-2011-JiangFH #data type #locality #network
Anomaly localization for network data streams with graph joint sparse PCA (RJ, HF, JH), pp. 886–894.
KDDKDD-2011-JinLA #nondeterminism #reliability
Discovering highly reliable subgraphs in uncertain graphs (RJ, LL, CCA), pp. 992–1000.
KDDKDD-2011-KangTSLF #named #scalability
GBASE: a scalable and general graph management system (UK, HT, JS, CYL, CF), pp. 1091–1099.
KDDKDD-2011-KongFY #classification
Dual active feature and sample selection for graph classification (XK, WF, PSY), pp. 654–662.
KDDKDD-2011-NamataKG #identification
Collective graph identification (GN, SK, LG), pp. 87–95.
KDDKDD-2011-ShiFZY #evolution
Discovering shakers from evolving entities via cascading graph inference (XS, WF, JZ, PSY), pp. 1001–1009.
KDDKDD-2011-ToivonenZHH
Compression of weighted graphs (HT, FZ, AH, AH), pp. 965–973.
KDDKDD-2011-TongHWKL #optimisation #ranking #scalability
Diversified ranking on large graphs: an optimization viewpoint (HT, JH, ZW, RK, CYL), pp. 1028–1036.
KDDKDD-2011-ZhouBS #approach #ranking
An iterated graph laplacian approach for ranking on manifolds (XZ, MB, NS), pp. 877–885.
KDIRKDIR-2011-ClariziaCSGN #novel #query
A Novel Query Expansion Technique based on a Mixed Graph of Terms (FC, FC, MDS, LG, PN), pp. 84–93.
KDIRKDIR-2011-DeruyverH #approach #consistency #image #information management #semantics
Semantic Graphs and Arc Consistency Checking — The Renewal of an Old Approach for Information Extraction from Images (AD, YH), pp. 515–522.
KDIRKDIR-2011-LiVM #learning #relational #using #visual notation
Unsupervised Handwritten Graphical Symbol Learning — Using Minimum Description Length Principle on Relational Graph (JL, CVG, HM), pp. 172–178.
KDIRKDIR-2011-SanJuan
Mapping Knowledge Domains — Combining Symbolic Relations with Graph Theory (ES), pp. 527–536.
KDIRKDIR-2011-Vanetik #algorithm #mining #performance
A Fast Algorithm for Mining Graphs of Prescribed Connectivity (NV), pp. 5–13.
KEODKEOD-2011-CruzN #ontology #xml
A Graph-based Tool for the Translation of XML Data to OWL-DL Ontologies (CC, CN), pp. 361–364.
KEODKEOD-2011-FukumotoS #classification #clustering #semantics #word
Semantic Classification of Unknown Words based on Graph-based Semi-supervised Clustering (FF, YS), pp. 37–46.
KEODKEOD-2011-YamasakiS
A Graph Manipulation System Abstracted from e-Learning (SY, MS), pp. 466–469.
RecSysRecSys-2011-LeeSKLL #multi #random #ranking #recommendation
Random walk based entity ranking on graph for multidimensional recommendation (SL, SiS, MK, DL, SgL), pp. 93–100.
SIGIRSIGIR-2011-HanSZ #web
Collective entity linking in web text: a graph-based method (XH, LS, JZ), pp. 765–774.
SIGIRSIGIR-2011-Jiang #query #semantics
Query expansion based on a semantic graph model (XJ), pp. 1315–1316.
SIGIRSIGIR-2011-JiYGHHZC #learning #query #web
Learning search tasks in queries and web pages via graph regularization (MJ, JY, SG, JH, XH, WVZ, ZC), pp. 55–64.
SIGIRSIGIR-2011-LeeHWHS #dataset #image #learning #multi #pipes and filters #scalability #using
Multi-layer graph-based semi-supervised learning for large-scale image datasets using mapreduce (WYL, LCH, GLW, WHH, YFS), pp. 1121–1122.
SIGIRSIGIR-2011-Li #learning
Learning for graphs with annotated edges (FL), pp. 1259–1260.
SIGIRSIGIR-2011-TangLWWL #ambiguity #network #social
A bipartite graph based social network splicing method for person name disambiguation (JT, QL, TW, JW, WL), pp. 1233–1234.
ICMTICMT-2011-BergmannURV #emf #modelling #query
A Graph Query Language for EMF Models (GB, ZU, IR, DV), pp. 167–182.
PEPMPEPM-J-2007-MollerS11 #program analysis #xml
XML graphs in program analysis (AM, MIS), pp. 492–515.
POPLPOPL-2011-PrountzosMPM #analysis #optimisation #parallel #source code
A shape analysis for optimizing parallel graph programs (DP, RM, KP, KSM), pp. 159–172.
ESEC-FSEESEC-FSE-2011-RamamurthiRS #analysis #data flow #probability #using
Probabilistic dataflow analysis using path profiles on structure graphs (AR, SR, YNS), pp. 512–515.
ICSEICSE-2011-KumarKRL #mining #sequence
Mining message sequence graphs (SK, SCK, AR, DL), pp. 91–100.
ICSEICSE-2011-Malik #analysis #using
Dynamic shape analysis of program heap using graph spectra (MZM), pp. 952–955.
SACSAC-2011-Jamil #query #unification #using
Computing subgraph isomorphic queries using structural unification and minimum graph structures (HMJ), pp. 1053–1058.
SACSAC-2011-KostakisKMM #comparison #using
Improved call graph comparison using simulated annealing (OK, JK, HM, KM), pp. 1516–1523.
SACSAC-2011-WangJZO #database #keyword
Exact top-k keyword search on graph databases (MW, LJ, LZ, TO), pp. 985–986.
SACSAC-2011-Zhang #analysis #constraints #geometry #problem
Well-constrained completion for under-constrained geometric constraint problem based on connectivity analysis of graph (GFZ), pp. 1094–1099.
SACSAC-2011-ZouaqGH #concept #using
Ontologizing concept maps using graph theory (AZ, DG, MH), pp. 1687–1692.
CGOCGO-2011-ChakrabartiBBJS #memory management #optimisation #runtime #transaction
The runtime abort graph and its application to software transactional memory optimization (DRC, PB, HJB, PGJ, RSS), pp. 42–53.
DATEDATE-2011-HausmansBC #data flow
Resynchronization of Cyclo-Static Dataflow graphs (JPHMH, MJGB, HC), pp. 1315–1320.
PPoPPPPoPP-2011-GrossetZLVH
Evaluating graph coloring on GPUs (AVPG, PZ, SL, SV, MWH), pp. 297–298.
PPoPPPPoPP-2011-HongKOO #algorithm
Accelerating CUDA graph algorithms at maximum warp (SH, SKK, TO, KO), pp. 267–276.
FASEFASE-2011-EhrigET #using #version control
A Formal Resolution Strategy for Operation-Based Conflicts in Model Versioning Using Graph Modifications (HE, CE, GT), pp. 202–216.
FASEFASE-2011-ZhangZL #api #complexity
Flow-Augmented Call Graph: A New Foundation for Taming API Complexity (QZ, WZ, MRL), pp. 386–400.
STOCSTOC-2011-BodirskyP #theorem
Schaefer’s theorem for graphs (MB, MP), pp. 655–664.
STOCSTOC-2011-ChristianoKMST #approximate #performance
Electrical flows, laplacian systems, and faster approximation of maximum flow in undirected graphs (PC, JAK, AM, DAS, SHT), pp. 273–282.
STOCSTOC-2011-Chuzhoy #algorithm #problem
An algorithm for the graph crossing number problem (JC), pp. 303–312.
STOCSTOC-2011-DemaineHK #algorithm #composition
Contraction decomposition in h-minor-free graphs and algorithmic applications (EDD, MH, KiK), pp. 441–450.
STOCSTOC-2011-FungHHP #framework
A general framework for graph sparsification (WSF, RH, NJAH, DP), pp. 71–80.
STOCSTOC-2011-ItalianoNSW #algorithm
Improved algorithms for min cut and max flow in undirected planar graphs (GFI, YN, PS, CWN), pp. 313–322.
STOCSTOC-2011-KawarabayashiW #algorithm #composition #proving
A simpler algorithm and shorter proof for the graph minor decomposition (KiK, PW), pp. 451–458.
STOCSTOC-2011-NewmanS
Every property of hyperfinite graphs is testable (IN, CS), pp. 675–684.
CSLCSL-2011-Kartzow #automaton
A Pumping Lemma for Collapsible Pushdown Graphs of Level 2 (AK), pp. 322–336.
ICSTSAT-2011-HeuleJB #performance
Efficient CNF Simplification Based on Binary Implication Graphs (MH, MJ, AB), pp. 201–215.
ICSTSAT-2011-SpeckenmeyerWP #approach #satisfiability
A Satisfiability-Based Approach for Embedding Generalized Tanglegrams on Level Graphs (ES, AW, SP), pp. 134–144.
TPDLECDL-2010-MarianLRV #ranking
Citation Graph Based Ranking in Invenio (LM, JYL, MR, MV), pp. 236–247.
HTHT-2010-CartledgeN #analysis
Analysis of graphs for digital preservation suitability (CLC, MLN), pp. 109–118.
SIGMODSIGMOD-2010-AchiezraGKS #keyword
Exploratory keyword search on data graphs (HA, KG, BK, YS), pp. 1163–1166.
SIGMODSIGMOD-2010-ChenWHY #in the cloud #scalability
Large graph processing in the cloud (RC, XW, BH, MY), pp. 1123–1126.
SIGMODSIGMOD-2010-JinBXCC #database #named #query #towards #visual notation
GBLENDER: towards blending visual query formulation and query processing in graph databases (CJ, SSB, XX, JC, BC), pp. 111–122.
SIGMODSIGMOD-2010-JinHWRX #constraints #database #reachability
Computing label-constraint reachability in graph databases (RJ, HH, HW, NR, YX), pp. 123–134.
SIGMODSIGMOD-2010-JinYW #classification #named #using
GAIA: graph classification using evolutionary computation (NJ, CY, WW), pp. 879–890.
SIGMODSIGMOD-2010-KhanYW #mining #proximity #scalability #towards
Towards proximity pattern mining in large graphs (AK, XY, KLW), pp. 867–878.
SIGMODSIGMOD-2010-MalewiczABDHLC #named #scalability
Pregel: a system for large-scale graph processing (GM, MHA, AJCB, JCD, IH, NL, GC), pp. 135–146.
SIGMODSIGMOD-2010-MortonBG #named #pipes and filters
ParaTimer: a progress indicator for MapReduce DAGs (KM, MB, DG), pp. 507–518.
SIGMODSIGMOD-2010-TaoSL
Finding maximum degrees in hidden bipartite graphs (YT, CS, JL), pp. 891–902.
SIGMODSIGMOD-2010-Wei #named #performance #query
TEDI: efficient shortest path query answering on graphs (FW0), pp. 99–110.
VLDBVLDB-2010-AggarwalLYJ #mining #on the
On Dense Pattern Mining in Graph Streams (CCA, YL, PSY, RJ), pp. 975–984.
VLDBVLDB-2010-FanLMTWW #pattern matching #polynomial
Graph Pattern Matching: From Intractable to Polynomial Time (WF, JL, SM, NT, YW, YW), pp. 264–275.
VLDBVLDB-2010-FanLMWW #morphism
Graph Homomorphism Revisited for Graph Matching (WF, JL, SM, HW, YW), pp. 1161–1172.
VLDBVLDB-2010-HanLPY #framework #named
iGraph: A Framework for Comparisons of Disk-Based Graph Indexing Techniques (WSH, JL, MDP, JXY), pp. 449–459.
VLDBVLDB-2010-MacropolS #clustering #scalability
Scalable Discovery of Best Clusters on Large Graphs (KM, AKS), pp. 693–702.
VLDBVLDB-2010-PotamiasBGK #nearest neighbour #nondeterminism
k-Nearest Neighbors in Uncertain Graphs (MP, FB, AG, GK), pp. 997–1008.
VLDBVLDB-2010-WickMM #database #probability #scalability
Scalable Probabilistic Databases with Factor Graphs and MCMC (MLW, AM, GM), pp. 794–804.
VLDBVLDB-2010-YildirimCZ #named #reachability #scalability
GRAIL: Scalable Reachability Index for Large Graphs (HY, VC, MJZ), pp. 276–284.
VLDBVLDB-2010-ZhangYJ #approximate #named #scalability
SAPPER: Subgraph Indexing and Approximate Matching in Large Graphs (SZ, JY, WJ), pp. 1185–1194.
VLDBVLDB-2010-ZhaoH #network #on the #optimisation #query #scalability
On Graph Query Optimization in Large Networks (PZ, JH), pp. 340–351.
VLDBVLDB-2011-RiceT10 #network #query #strict
Graph Indexing of Road Networks for Shortest Path Queries with Label Restrictions (MNR, VJT), pp. 69–80.
VLDBVLDB-2011-WangZTT10 #on the
On Triangulation-based Dense Neighborhood Graphs Discovery (NW, JZ, KLT, AKHT), pp. 58–68.
ITiCSEITiCSE-2010-Kasyanov #tool support
Support tools for graphs in computer science (VNK), p. 315.
ICPCICPC-2010-ChenR #case study #dependence #feature model #using
Case Study of Feature Location Using Dependence Graph, after 10 Years (KC, VR), pp. 1–3.
ICSMEICSM-2010-BhattacharyaN #debugging #fine-grained #incremental #learning #multi
Fine-grained incremental learning and multi-feature tossing graphs to improve bug triaging (PB, IN), pp. 1–10.
ICSMEICSM-2010-LiQJW #automation #generative #testing
Automatic test case selection and generation for regression testing of composite service based on extensible BPEL flow graph (BL, DQ, SJ, DW), pp. 1–10.
ICSMEICSM-2010-SaleckerG #testing #using
Pairwise test set calculation using k-partite graphs (ES, SG), pp. 1–5.
SCAMSCAM-2010-AllierVDS #metric
Deriving Coupling Metrics from Call Graphs (SA, SV, BD, HAS), pp. 43–52.
CIAACIAA-2010-EpifanioFGMS #lazy evaluation #on the
On Lazy Representations and Sturmian Graphs (CE, CF, AG, FM, JS), pp. 125–134.
CIAACIAA-2010-Neider #automation #game studies #reachability
Reachability Games on Automatic Graphs (DN), pp. 222–230.
DLTDLT-2010-HalldorssonKP #word
Graphs Capturing Alternations in Words (MMH, SK, AVP), pp. 436–437.
DLTDLT-2010-HauboldLM #morphism #problem #word
Compressed Conjugacy and the Word Problem for Outer Automorphism Groups of Graph Groups (NH, ML, CM), pp. 218–230.
ICALPICALP-v1-2010-CaiCL #morphism #theorem
Graph Homomorphisms with Complex Values: A Dichotomy Theorem (JyC, XC, PL), pp. 275–286.
ICALPICALP-v1-2010-Georgiadis #testing
Testing 2-Vertex Connectivity and Computing Pairs of Vertex-Disjoint s-t Paths in Digraphs (LG), pp. 738–749.
ICALPICALP-v1-2010-KoblerKLV #canonical #representation
Interval Graphs: Canonical Representation in Logspace (JK, SK, BL, OV), pp. 384–395.
ICALPICALP-v1-2010-RueST #programming
Dynamic Programming for Graphs on Surfaces (JR, IS, DMT), pp. 372–383.
ICALPICALP-v2-2010-ChechikEPP #reliability
Sparse Reliable Graph Backbones (SC, YE, BPS, DP), pp. 261–272.
SEFMSEFM-2010-BarrosCHP #slicing
Assertion-based Slicing and Slice Graphs (JBB, DCdC, PRH, JSP), pp. 93–102.
SEFMSEFM-2010-GoldsmithC
Refinement-Friendly Bigraphs and Spygraphs (MG, SC), pp. 203–207.
AIIDEAIIDE-2010-FurtakB #complexity #game studies #on the
On the Complexity of Two-Player Attrition Games Played on Graphs (TF, MB).
GT-VMTGT-VMT-2010-BlumeBK #invariant
Recognizable Graph Languages for Checking Invariants (CB, HJSB, BK).
GT-VMTGT-VMT-2010-GrohmannM #algebra
Graph Algebras for Bigraphs (DG, MM).
GT-VMTGT-VMT-2010-HermannCEK #analysis #equivalence #performance #permutation #petri net
Efficient Analysis of Permutation Equivalence of Graph Derivations Based on Petri Nets (FH, AC, HE, BK).
GT-VMTGT-VMT-2010-MolR #on the #order
On A Graph Formalism for Ordered Edges (MdM, AR).
ICGTICGT-2010-Blume #verification
Recognizable Graph Languages for the Verification of Dynamic Systems (CB), pp. 384–387.
ICGTICGT-2010-Jurack #emf #inheritance #modelling
Composite EMF Modeling Based on Typed Graphs with Inheritance and Containment Structures (SJ), pp. 397–399.
ICGTICGT-2010-JurackT #component #concept #inheritance
A Component Concept for Typed Graphs with Inheritance and Containment Structures (SJ, GT), pp. 187–202.
ICGTICGT-2010-PoskittP #calculus #hoare #source code
A Hoare Calculus for Graph Programs (CMP, DP), pp. 139–154.
ICGTICGT-2010-Radke #correctness #source code
Correctness of Graph Programs Relative to HR + Conditions (HR), pp. 410–412.
ICGTICGT-2010-TaentzerELW #detection #version control
Conflict Detection for Model Versioning Based on Graph Modifications (GT, CE, PL, MW), pp. 171–186.
CHICHI-2010-McGookinRB #interactive #using
Clutching at straws: using tangible interaction to provide non-visual access to graphs (DKM, ER, SAB), pp. 1715–1724.
SOFTVISSOFTVIS-2010-MedaniHBKLMPSY #visualisation
Graph works — pilot graph theory visualization tool (DM, GH, CB, PK, NL, TM, SP, RS, AY), pp. 205–206.
CAiSECAiSE-2010-LyRD #design #information management #verification
Design and Verification of Instantiable Compliance Rule Graphs in Process-Aware Information Systems (LTL, SRM, PD), pp. 9–23.
ICEISICEIS-DISI-2010-Chein #information management #reasoning #representation
Graph-based Knowledge Representation and Reasoning (MC), pp. 17–21.
ICEISICEIS-ISAS-2010-ArtignanH #named #tool support #visualisation
STOOG — Style-Sheets-based Toolkit for Graph Visualization (GA, MH), pp. 123–131.
CIKMCIKM-2010-CaiP #named #query #reachability #scalability
Path-hop: efficiently indexing large graphs for reachability queries (JC, CKP), pp. 119–128.
CIKMCIKM-2010-ChengOWZ #named #web #web service
WS-GraphMatching: a web service tool for graph matching (QC, MO, JW, AZ), pp. 1949–1950.
CIKMCIKM-2010-DeyJ #approach #database #query #reachability #scalability
A hierarchical approach to reachability query answering in very large graph databases (SKD, HMJ), pp. 1377–1380.
CIKMCIKM-2010-GaoQJWY #performance
Fast top-k simple shortest paths discovery in graphs (JG, HQ, XJ, TW, DY), pp. 509–518.
CIKMCIKM-2010-GubichevBSW #estimation #performance #scalability
Fast and accurate estimation of shortest paths in large graphs (AG, SJB, SS, GW), pp. 499–508.
CIKMCIKM-2010-HuangSN #query #refinement #using #word
Query model refinement using word graphs (YH, LS, JYN), pp. 1453–1456.
CIKMCIKM-2010-PobleteBMB #image #query #retrieval #semantic gap #using #web
Visual-semantic graphs: using queries to reduce the semantic gap in web image retrieval (BP, BB, MM, JMB), pp. 1553–1556.
CIKMCIKM-2010-SongH #independence #rdf
Domain-independent entity coreference in RDF graphs (DS, JH), pp. 1821–1824.
CIKMCIKM-2010-SunPL
Support elements in graph structured schema reintegration (XS, RP, MKL), pp. 1361–1364.
CIKMCIKM-2010-ZhangLY #named
SUMMA: subgraph matching in massive graphs (SZ, SL, JY), pp. 1285–1288.
CIKMCIKM-2010-ZhengGYXBSHY #community #interactive #topic
A topical link model for community discovery in textual interaction graph (GZ, JG, LY, SX, SB, ZS, DH, YY), pp. 1613–1616.
ICMLICML-2010-Cesa-BianchiGVZ #predict #random
Random Spanning Trees and the Prediction of Weighted Graphs (NCB, CG, FV, GZ), pp. 175–182.
ICMLICML-2010-GavishNC #learning #multi #theory and practice
Multiscale Wavelets on Trees, Graphs and High Dimensional Data: Theory and Applications to Semi Supervised Learning (MG, BN, RRC), pp. 367–374.
ICMLICML-2010-LiuHC #learning #scalability
Large Graph Construction for Scalable Semi-Supervised Learning (WL, JH, SFC), pp. 679–686.
ICMLICML-2010-LiuNLL #analysis #learning #relational
Learning Temporal Causal Graphs for Relational Time-Series Analysis (YL, ANM, ACL, YL), pp. 687–694.
ICMLICML-2010-LiuY #robust
Robust Graph Mode Seeking by Graph Shift (HL, SY), pp. 671–678.
ICMLICML-2010-TingHJ #analysis #convergence
An Analysis of the Convergence of Graph Laplacians (DT, LH, MIJ), pp. 1079–1086.
ICPRICPR-2010-AslanAFRAX #3d #segmentation #using
3D Vertebral Body Segmentation Using Shape Based Graph Cuts (MSA, AMA, AAF, HMR, BA, PX), pp. 3951–3954.
ICPRICPR-2010-BaldacciBD #3d #algorithm #bound #design #framework #segmentation
Oriented Boundary Graph: A Framework to Design and Implement 3D Segmentation Algorithms (FB, AJPB, JPD), pp. 1116–1119.
ICPRICPR-2010-BardajiFS #distance #edit distance
Computing the Barycenter Graph by Means of the Graph Edit Distance (IB, MF, AS), pp. 962–965.
ICPRICPR-2010-BauerEOBKFHN #approach #bound #estimation #performance #robust
A Fast and Robust Graph-Based Approach for Boundary Estimation of Fiber Bundles Relying on Fractional Anisotropy Maps (MHAB, JE, TO, SB, JK, BF, HKH, CN), pp. 4016–4019.
ICPRICPR-2010-BonevEGB #feature model
Information-theoretic Feature Selection from Unattributed Graphs (BB, FE, DG, SB), pp. 930–933.
ICPRICPR-2010-ChenF #learning
Semi-supervised Graph Learning: Near Strangers or Distant Relatives (WC, GF), pp. 3368–3371.
ICPRICPR-2010-ChowdhuryCGR #using #video
Cell Tracking in Video Microscopy Using Bipartite Graph Matching (ASC, RC, MG, NR), pp. 2456–2459.
ICPRICPR-2010-CordellaSMS #order #traversal
Writing Order Recovery from Off-Line Handwriting by Graph Traversal (LPC, CDS, AM, AS), pp. 1896–1899.
ICPRICPR-2010-FerrerB #algorithm #approximate
An Iterative Algorithm for Approximate Median Graph Computation (MF, HB), pp. 1562–1565.
ICPRICPR-2010-FreireCF #approach #generative #problem
A Column Generation Approach for the Graph Matching Problem (ASF, RMCJ, CEF), pp. 1088–1091.
ICPRICPR-2010-HaugeardPG #image #kernel #retrieval #taxonomy
Kernel on Graphs Based on Dictionary of Paths for Image Retrieval (JEH, SPF, PHG), pp. 2965–2968.
ICPRICPR-2010-IgelmoSF #representation
A Conductance Electrical Model for Representing and Matching Weighted Undirected Graphs (MI, AS, MF), pp. 958–961.
ICPRICPR-2010-JainO #consistency
Consistent Estimator of Median and Mean Graph (BJJ, KO), pp. 1032–1035.
ICPRICPR-2010-JouiliTL #algorithm #clustering
Median Graph Shift: A New Clustering Algorithm for Graph Domain (SJ, ST, VL), pp. 950–953.
ICPRICPR-2010-LeeCL #algorithm #data-driven #markov #monte carlo #using
A Graph Matching Algorithm Using Data-Driven Markov Chain Monte Carlo Sampling (JL, MC, KML), pp. 2816–2819.
ICPRICPR-2010-LeskoKNGTVV #segmentation
Live Cell Segmentation in Fluorescence Microscopy via Graph Cut (ML, ZK, AN, IG, ZT, LVJ, LV), pp. 1485–1488.
ICPRICPR-2010-RevaudLAB #learning #performance #recognition #robust
Learning an Efficient and Robust Graph Matching Procedure for Specific Object Recognition (JR, GL, YA, AB), pp. 754–757.
ICPRICPR-2010-RichiardiVRB #classification #sequence
Vector Space Embedding of Undirected Graphs with Fixed-cardinality Vertex Sequences for Classification (JR, DVDV, KR, HB), pp. 902–905.
ICPRICPR-2010-SanromaAS #approach #using
A Discrete Labelling Approach to Attributed Graph Matching Using SIFT Features (GS, RA, FS), pp. 954–957.
ICPRICPR-2010-WangLR #clustering
Combining Real and Virtual Graphs to Enhance Data Clustering (LW, CL, KR), pp. 790–793.
ICPRICPR-2010-ZhangK10a #detection #using
Text Detection Using Edge Gradient and Graph Spectrum (JZ, RK), pp. 3979–3982.
ICPRICPR-2010-ZhangYWWXHY #multi #recognition
Multi-class Graph Boosting with Subgraph Sharing for Object Recognition (BZ, GY, YW, WW, JX, GH, YY), pp. 1541–1544.
ICPRICPR-2010-ZhouZP #approach #named
Lipreading: A Graph Embedding Approach (ZZ, GZ, MP), pp. 523–526.
KDDKDD-2010-FeiH #classification #functional
Boosting with structure information in the functional space: an application to graph classification (HF, JH), pp. 643–652.
KDDKDD-2010-HeFLC #parallel #scalability
Parallel SimRank computation on large graphs with iterative aggregation (GH, HF, CL, HC), pp. 543–552.
KDDKDD-2010-HendersonEFALMPT #approach #forensics #metric #mining #multi
Metric forensics: a multi-level approach for mining volatile graphs (KH, TER, CF, LA, LL, KM, BAP, HT), pp. 163–172.
KDDKDD-2010-KongY #classification #feature model
Semi-supervised feature selection for graph classification (XK, PSY), pp. 793–802.
KDDKDD-2010-MaxwellBR #memory management #mining #using
Diagnosing memory leaks using graph mining on heap dumps (EKM, GB, NR), pp. 115–124.
KDDKDD-2010-RothBDFHLLMM #social #using
Suggesting friends using the implicit social graph (MR, ABD, DD, GF, IH, AL, NL, YM, RM), pp. 233–242.
KDDKDD-2010-SarkarM #nearest neighbour #performance
Fast nearest-neighbor search in disk-resident graphs (PS, AWM), pp. 513–522.
KDDKDD-2010-TanTSLW #social
Social action tracking via noise tolerant time-varying factor graphs (CT, JT, JS, QL, FW), pp. 1049–1058.
KDDKDD-2010-XiangYZCZYS #recommendation
Temporal recommendation on graphs via long- and short-term preference fusion (LX, QY, SZ, LC, XZ, QY, JS), pp. 723–732.
KDDKDD-2010-ZouGL #database #nondeterminism #probability #semantics
Discovering frequent subgraphs over uncertain graph databases under probabilistic semantics (ZZ, HG, JL), pp. 633–642.
KDIRKDIR-2010-KKD #keyword #rdf
Answer Graph Construction for Keyword Search on Graph Structured(RDF) Data (PK, SPK, DD), pp. 162–167.
KDIRKDIR-2010-MuA #classification #multi
Proximity-based Graph Embeddings for Multi-label Classification (TM, SA), pp. 74–84.
KRKR-2010-Li #representation
A Layered Graph Representation for Complex Regions (SL).
RecSysRecSys-2010-DesarkarSM #collaboration #predict #rating
Aggregating preference graphs for collaborative rating prediction (MSD, SS, PM), pp. 21–28.
RecSysRecSys-2010-MoldvayBFS #clustering #named #recommendation #semantics #social
Tagmantic: a social recommender service based on semantic tag graphs and tag clusters (JM, IB, AF, MS), pp. 345–346.
SIGIRSIGIR-2010-BordinoCDG #query #similarity
Query similarity by projecting the query-flow graph (IB, CC, DD, AG), pp. 515–522.
SIGIRSIGIR-2010-PhamMM #categorisation #image #modelling #visual notation
Spatial relationships in visual graph modeling for image categorization (TTP, PM, LM), pp. 729–730.
ICMTICMT-2010-VoigtH #distance #edit distance #metamodelling
Metamodel Matching Based on Planar Graph Edit Distance (KV, TH), pp. 245–259.
PLEASEPLEASE-2010-MamanB #named #product line #towards
SPLGraph: towards a graph-based formalism for software product lines (IM, GB), pp. 40–47.
OOPSLAOOPSLA-2010-NguyenNWNKN #adaptation #api #approach
A graph-based approach to API usage adaptation (HAN, TTN, GWJ, ATN, MK, TNN), pp. 302–321.
LOPSTRLOPSTR-2010-DanvyZ #combinator #reduction
Three Syntactic Theories for Combinatory Graph Reduction (OD, IZ), pp. 1–20.
LOPSTRLOPSTR-2010-GiorginoSMP #algorithm #verification
Verification of the Schorr-Waite Algorithm — From Trees to Graphs (MG, MS, RM, MP), pp. 67–83.
LOPSTRLOPSTR-2010-LlorensOST #csp #generative #process
Graph Generation to Statically Represent CSP Processes (ML, JO, JS, ST), pp. 52–66.
PPDPPPDP-2010-TekleGL #datalog #optimisation #query
Graph queries through datalog optimizations (KTT, MG, YAL), pp. 25–34.
ASEASE-2010-Letarte #analysis #interprocedural #model checking #precise #representation
Model checking graph representation of precise boolean inter-procedural flow analysis (DL), pp. 511–516.
ASEASE-2010-WangLCZMY #dependence #query
Matching dependence-related queries in the system dependence graph (XW, DL, JC, LZ, HM, JXY), pp. 457–466.
SACSAC-2010-CiraciBA #constraints #verification
Graph-based verification of static program constraints (SC, PvdB, MA), pp. 2265–2272.
SACSAC-2010-JanssenPW #similarity
Estimating node similarity from co-citation in a spatial graph model (JJ, PP, RW), pp. 1329–1333.
SACSAC-2010-LeeJL #detection #using
Detecting metamorphic malwares using code graphs (JL, KJ, HL), pp. 1970–1977.
SACSAC-2010-LlorensOST #algorithm #control flow
An algorithm to generate the context-sensitive synchronized control flow graph (ML, JO, JS, ST), pp. 2144–2148.
SACSAC-2010-OssaPSG #algorithm #low cost #predict #web
Referrer graph: a low-cost web prediction algorithm (BdlO, AP, JS, JAG), pp. 831–838.
SACSAC-2010-PortugalR #algorithm #clustering #multi #using
MSP algorithm: multi-robot patrolling based on territory allocation using balanced graph partitioning (DP, RPR), pp. 1271–1276.
LDTALDTA-2010-CortesiH #dependence #semantics #slicing
Dependence condition graph for semantics-based abstract program slicing (AC, RH), p. 4.
CGOCGO-2010-OdairaNIKN
Coloring-based coalescing for graph coloring register allocation (RO, TN, TI, HK, TN), pp. 160–169.
DACDAC-2010-LinL
Double patterning lithography aware gridless detailed routing with innovative conflict graph (YHL, YLL), pp. 398–403.
DACDAC-2010-ParkBWM #debugging #locality #named #using
BLoG: post-silicon bug localization in processors using bug localization graphs (SBP, AB, HW, SM), pp. 368–373.
DATEDATE-2010-HuanYCM #energy
Energy-oriented dynamic SPM allocation based on time-slotted Cache conflict graph (WH, ZY, MC, LM), pp. 598–601.
DATEDATE-2010-IqbalSH10a #estimation #execution #monte carlo #named
DAGS: Distribution agnostic sequential Monte Carlo scheme for task execution time estimation (NI, MAS, JH), pp. 1645–1648.
DATEDATE-2010-PerezSF #data flow #optimisation #relational
Optimizing Data-Flow Graphs with min/max, adding and relational operations (JP, PS, VF), pp. 1361–1364.
DATEDATE-2010-SrinivasJ #clustering #performance
Clock gating approaches by IOEX graphs and cluster efficiency plots (JS, SJ), pp. 638–641.
DATEDATE-2010-WiggersBGB
Simultaneous budget and buffer size computation for throughput-constrained task graphs (MW, MB, MG, TB), pp. 1669–1672.
HPDCHPDC-2010-LiewAHH #data type #distributed #optimisation #parallel #streaming #towards #using
Towards optimising distributed data streaming graphs using parallel streams (CSL, MPA, JIvH, LH), pp. 725–736.
ISMMISMM-2010-BegB #approach
A graph theoretic approach to cache-conscious placement of data for direct mapped caches (MB, PvB), pp. 113–120.
PDPPDP-2010-BittencourtSM #algorithm #lookahead #scheduling #using
DAG Scheduling Using a Lookahead Variant of the Heterogeneous Earliest Finish Time Algorithm (LFB, RS, ERMM), pp. 27–34.
PDPPDP-2010-SunWC #approach #clustering #coordination #network
A Graph Clustering Approach to Computing Network Coordinates (YS, BW, KC), pp. 129–136.
ESOPESOP-2010-BlazyRA #verification
Formal Verification of Coalescing Graph-Coloring Register Allocation (SB, BR, AWA), pp. 145–164.
ESOPESOP-2010-LavironCR
Separating Shape Graphs (VL, BYEC, XR), pp. 387–406.
STOCSTOC-2010-BateniHM #approximate #bound
Approximation schemes for steiner forest on planar graphs and graphs of bounded treewidth (MB, MH, DM), pp. 211–220.
STOCSTOC-2010-BayatiGT #approach #combinator #random #scalability
Combinatorial approach to the interpolation method and scaling limits in sparse random graphs (MB, DG, PT), pp. 105–114.
STOCSTOC-2010-DuanP
Connectivity oracles for failure prone graphs (RD, SP), pp. 465–474.
STOCSTOC-2010-GoelKK
Perfect matchings in o(n log n) time in regular bipartite graphs (AG, MK, SK), pp. 39–46.
STOCSTOC-2010-KawarabayashiW #algorithm #proving #theorem
A shorter proof of the graph minor algorithm: the unique linkage theorem (KiK, PW), pp. 687–694.
STOCSTOC-2010-Madry #algorithm #approximate #multi #performance #problem
Faster approximation schemes for fractional multicommodity flow problems via dynamic graph algorithms (AM), pp. 121–130.
STOCSTOC-2010-RaghavendraS #game studies
Graph expansion and the unique games conjecture (PR, DS), pp. 755–764.
STOCSTOC-2010-RaghavendraST #approximate #parametricity
Approximations for the isoperimetric and spectral profile of graphs and related parameters (PR, DS, PT), pp. 631–640.
CAVCAV-2010-KahlonW #concurrent #debugging #detection #precise #source code
Universal Causality Graphs: A Precise Happens-Before Model for Detecting Bugs in Concurrent Programs (VK, CW), pp. 434–449.
ICSTICST-2010-NguyenWR #named
GraphSeq: A Graph Matching Tool for the Extraction of Mobility Patterns (MDN, HW, NR), pp. 195–204.
IJCARIJCAR-2010-BensaidCP #integer
Perfect Discrimination Graphs: Indexing Terms with Integer Exponents (HB, RC, NP), pp. 369–383.
LICSLICS-2010-Grohe #fixpoint #polynomial
Fixed-Point Definability and Polynomial Time on Graphs with Excluded Minors (MG), pp. 179–188.
LICSLICS-2010-Laubner #polynomial
Capturing Polynomial Time on Interval Graphs (BL), pp. 199–208.
DocEngDocEng-2009-Hassan09a #documentation #interactive #named #using
GraphWrap: a system for interactive wrapping of pdf documents using graph matching techniques (TH), pp. 247–248.
ICDARICDAR-2009-BodicLAHLK #detection #integer #linear #programming #using
Symbol Detection Using Region Adjacency Graphs and Integer Linear Programming (PLB, HL, SA, PH, YL, AK), pp. 1320–1324.
ICDARICDAR-2009-GacebELE #automation #documentation #recognition
Graph b-Coloring for Automatic Recognition of Documents (DG, VE, FL, HE), pp. 261–265.
ICDARICDAR-2009-Hassan #documentation #using
User-Guided Wrapping of PDF Documents Using Graph Matching Techniques (TH), pp. 631–635.
ICDARICDAR-2009-LuqmanBR #classification #network #recognition #using
Graphic Symbol Recognition Using Graph Based Signature and Bayesian Network Classifier (MML, TB, JYR), pp. 1325–1329.
ICDARICDAR-2009-Schambach #recognition
Recurrent HMMs and Cursive Handwriting Recognition Graphs (MPS), pp. 1146–1150.
ICDARICDAR-2009-SidereHR #classification #representation
Vector Representation of Graphs: Application to the Classification of Symbols and Letters (NS, PH, JYR), pp. 681–685.
JCDLJCDL-2009-LiC #approach #kernel #machine learning #predict #recommendation
Recommendation as link prediction: a graph kernel-based machine learning approach (XL, HC), pp. 213–216.
SIGMODSIGMOD-2009-NeumannW #rdf #scalability
Scalable join processing on very large RDF graphs (TN, GW), pp. 627–640.
VLDBVLDB-2009-AggarwalXY #named
GConnect: A Connectivity Index for Massive Disk-resident Graphs (CCA, YX, PSY), pp. 862–873.
VLDBVLDB-2009-BrauerBHSMF #documentation #named #retrieval
RankIE: Document Retrieval on Ranked Entity Graphs (FB, WMB, GH, MS, AM, FF), pp. 1578–1581.
VLDBVLDB-2009-ChenLFCYH #mining #random #summary
Mining Graph Patterns Efficiently via Randomized Summaries (CC, CXL, MF, MC, XY, JH), pp. 742–753.
VLDBVLDB-2009-CormodeSBK #network #social
Class-based graph anonymization for social network data (GC, DS, SB, BK), pp. 766–777.
VLDBVLDB-2009-HasanZ
Output Space Sampling for Graph Patterns (MAH, MJZ), pp. 730–741.
VLDBVLDB-2009-ZengTWFZ #approximate #distance #edit distance
Comparing Stars: On Approximating Graph Edit Distance (ZZ, AKHT, JW, JF, LZ), pp. 25–36.
VLDBVLDB-2009-ZhouCY #clustering
Graph Clustering Based on Structural/Attribute Similarities (YZ, HC, JXY), pp. 718–729.
VLDBVLDB-2009-ZouCO #database #named #query #scalability
DistanceJoin: Pattern Match Query In a Large Graph Database (LZ, LC, MTÖ), pp. 886–897.
ITiCSEITiCSE-2009-BryfczynskiP #named
GraphPad: a graph creation tool for CS2/CS7 (SPB, RPP), p. 389.
CSMRCSMR-2009-BittencourtG #algorithm #architecture #clustering #comparison
Comparison of Graph Clustering Algorithms for Recovering Software Architecture Module Views (RAB, DDSG), pp. 251–254.
ICPCICPC-2009-SamiaL #architecture #scalability #towards #visualisation
Towards pie tree visualization of graphs and large software architectures (MS, ML), pp. 301–302.
ICPCICPC-2009-SimRC #comprehension #question
Structure transition graphs: An ECG for program comprehension? (SES, SR, LC), pp. 303–304.
ICSMEICSM-2009-LinZZ #aspectj #incremental
Incremental call graph reanalysis for AspectJ software (YL, SZ, JZ), pp. 306–315.
ICSMEICSM-2009-WangLSKKL #approach #combinator #navigation #web
A combinatorial approach to building navigation graphs for dynamic web applications (WW, YL, SS, RK, RK, JL), pp. 211–220.
WCREWCRE-1999-HigoK99a #clone detection #dependence #detection #quality
Enhancing Quality of Code Clone Detection with Program Dependency Graph (YH, SK), pp. 315–316.
WCREWCRE-1999-Kpodjedo99a #approximate #re-engineering
Approximate Graph Matching in Software Engineering (SK), pp. 295–298.
CIAACIAA-2009-Fujiyoshi #automaton #recognition
Recognition of a Spanning Tree of Directed Acyclic Graphs by Tree Automata (AF), pp. 105–114.
DLTDLT-2009-CampanoniC #control flow
Traces of Control-Flow Graphs (SC, SCR), pp. 156–169.
ICALPICALP-v1-2009-AroraSW #case study #towards
Towards a Study of Low-Complexity Graphs (SA, DS, AW), pp. 119–131.
ICALPICALP-v1-2009-ChekuriK #reduction
A Graph Reduction Step Preserving Element-Connectivity and Applications (CC, NK), pp. 254–265.
ICALPICALP-v1-2009-DemaineHK #algorithm #approximate
Approximation Algorithms via Structural Results for Apex-Minor-Free Graphs (EDD, MH, KiK), pp. 316–327.
ICALPICALP-v1-2009-DemaineHK09a
Node-Weighted Steiner Tree and Group Steiner Tree in Planar Graphs (EDD, MH, PNK), pp. 328–340.
ICALPICALP-v1-2009-WeimannY
Computing the Girth of a Planar Graph in O(n logn) Time (OW, RY), pp. 764–773.
ICALPICALP-v1-2009-YeB
Elimination Graphs (YY, AB), pp. 774–785.
ICALPICALP-v2-2009-AhnG
Graph Sparsification in the Semi-streaming Model (KJA, SG), pp. 328–338.
ICALPICALP-v2-2009-CooperIKK #random #using
Derandomizing Random Walks in Undirected Graphs Using Locally Fair Exploration Strategies (CC, DI, RK, AK), pp. 411–422.
ICALPICALP-v2-2009-KorulaP #algorithm #problem
Algorithms for Secretary Problems on Graphs and Hypergraphs (NK, MP), pp. 508–520.
LATALATA-2009-Courcelle #algorithm #higher-order #logic #monad
Monadic Second-Order Logic for Graphs: Algorithmic and Language Theoretical Applications (BC), pp. 19–22.
SEFMSEFM-2009-DangG #metamodelling #modelling #precise
Precise Model-Driven Transformations Based on Graphs and Metamodels (DHD, MG), pp. 307–316.
CEFPCEFP-2009-TothBHLTK #behaviour #dependence #erlang #impact analysis #source code #using
Impact Analysis of Erlang Programs Using Behaviour Dependency Graphs (MT, IB, ZH, LL, MT, TK), pp. 372–390.
GT-VMTGT-VMT-2009-BruniL
Ten virtues of structured graphs (RB, ALL), pp. 3–22.
CHICHI-2009-HoltenW #case study #user study #visualisation
A user study on visualizing directed edges in graphs (DH, JJvW), pp. 2299–2308.
CHICHI-2009-Stewarts #sketching
Graph sketcher: extending illustration to quantitative graphs (RS, MMCS), pp. 1113–1116.
HCIHCI-NIMT-2009-ItoMT #3d #visualisation
Sphere Anchored Map: A Visualization Technique for Bipartite Graphs in 3D (TI, KM, JT), pp. 811–820.
HCIHIMI-DIE-2009-VandrommeDPC #interactive #semantics
An Interactive System Based on Semantic Graphs (JV, SD, PP, CC), pp. 638–647.
ICEISICEIS-AIDSS-2009-YangLSKCGP #learning
Graph Structure Learning for Task Ordering (YY, AL, HS, BK, CMC, RG, KP), pp. 164–169.
ICEISICEIS-DISI-2009-Chen
Directed Acyclic Graphs and Disjoint Chains (YC), pp. 17–24.
CIKMCIKM-2009-AnastasakosHKR #approach #collaboration #recommendation #using
A collaborative filtering approach to ad recommendation using the query-ad click graph (TA, DH, SK, HR), pp. 1927–1930.
CIKMCIKM-2009-BaragliaCDNPS #query
Aging effects on query flow graphs for query suggestion (RB, CC, DD, FMN, RP, FS), pp. 1947–1950.
CIKMCIKM-2009-ChengKN #performance #query #scalability
Efficient processing of group-oriented connection queries in a large graph (JC, YK, WN), pp. 1481–1484.
CIKMCIKM-2009-FeiH #kernel
L2 norm regularized feature kernel regression for graph data (HF, JH), pp. 593–600.
CIKMCIKM-2009-FletcherB #performance #rdf #scalability
Scalable indexing of RDF graphs for efficient join processing (GHLF, PWB), pp. 1513–1516.
CIKMCIKM-2009-HeLL #learning
Graph-based transfer learning (JH, YL, RDL), pp. 937–946.
CIKMCIKM-2009-HuangSN #documentation #word
Smoothing document language model with local word graph (YH, LS, JYN), pp. 1943–1946.
CIKMCIKM-2009-JinYW #classification
Graph classification based on pattern co-occurrence (NJ, CY, WW), pp. 573–582.
CIKMCIKM-2009-KimPDG #classification #web
Improving web page classification by label-propagation over click graphs (SMK, PP, LD, SG), pp. 1077–1086.
CIKMCIKM-2009-PattanasriMM #comprehension #named #random
ComprehEnRank: estimating comprehension in classroom by absorbing random walks on a cognitive graph (NP, MM, MM), pp. 1769–1772.
CIKMCIKM-2009-SunMG #independence #information retrieval #mining
Independent informative subgraph mining for graph information retrieval (BS, PM, CLG), pp. 563–572.
CIKMCIKM-2009-SunMG09a #learning #online #rank
Learning to rank graphs for online similar graph search (BS, PM, CLG), pp. 1871–1874.
CIKMCIKM-2009-TongQJF #interactive #named #performance #proximity #query
iPoG: fast interactive proximity querying on graphs (HT, HQ, HJ, CF), pp. 1673–1676.
CIKMCIKM-2009-ZhengDG #crawling
Graph-based seed selection for web-scale crawlers (SZ, PD, CLG), pp. 1967–1970.
CIKMCIKM-2009-ZhongL #named #semistructured data
3se: a semi-structured search engine for heterogeneous data in graph model (MZ, ML), pp. 1405–1408.
CIKMCIKM-2009-ZouLGZ #mining #nondeterminism
Frequent subgraph pattern mining on uncertain graph data (ZZ, JL, HG, SZ), pp. 583–592.
ECIRECIR-2009-Pablo-SanchezM #classification
Building a Graph of Names and Contextual Patterns for Named Entity Classification (CdPS, PM), pp. 530–537.
ECIRECIR-2009-PapadopoulosMKB #recommendation
Lexical Graphs for Improved Contextual Ad Recommendation (SP, FM, YK, BB), pp. 216–227.
ICMLICML-2009-BuhlerH #clustering
Spectral clustering based on the graph p-Laplacian (TB, MH), pp. 81–88.
ICMLICML-2009-DaitchKS
Fitting a graph to vector data (SID, JAK, DAS), pp. 201–208.
ICMLICML-2009-JacobOV
Group lasso with overlap and graph lasso (LJ, GO, JPV), pp. 433–440.
ICMLICML-2009-JebaraWC #learning
Graph construction and b-matching for semi-supervised learning (TJ, JW, SFC), pp. 441–448.
ICMLICML-2009-MesmayRVP #library #optimisation #performance
Bandit-based optimization on graphs with application to library performance tuning (FdM, AR, YV, MP), pp. 729–736.
ICMLICML-2009-NowozinJ #clustering #learning #linear #programming
Solution stability in linear programming relaxations: graph partitioning and unsupervised learning (SN, SJ), pp. 769–776.
KDDKDD-2009-AsurP #analysis #approach #interactive
A viewpoint-based approach for interaction graph analysis (SA, SP), pp. 79–88.
KDDKDD-2009-DengLK #algorithm
A generalized Co-HITS algorithm and its application to bipartite graphs (HD, MRL, IK), pp. 239–248.
KDDKDD-2009-LiuKJ #learning #monitoring
Learning dynamic temporal graphs for oil-production equipment monitoring system (YL, JRK, OJ), pp. 1225–1234.
KDDKDD-2009-Macskassy #empirical #learning #metric #using
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data (SAM), pp. 597–606.
KDDKDD-2009-MaunzHK #mining #refinement #scalability #using
Large-scale graph mining using backbone refinement classes (AM, CH, SK), pp. 617–626.
KDDKDD-2009-McGlohonBASF #detection #named
SNARE: a link analytic system for graph labeling and risk detection (MM, SB, MGA, DMS, CF), pp. 1265–1274.
KDDKDD-2009-SatuluriP #clustering #community #probability #scalability #using
Scalable graph clustering using stochastic flows: applications to community discovery (VS, SP), pp. 737–746.
KDDKDD-2009-TsourakakisKMF #named
DOULION: counting triangles in massive graphs with a coin (CET, UK, GLM, CF), pp. 837–846.
KDDKDD-2009-YinLMH #classification #social #web
Exploring social tagging graph for web object classification (ZY, RL, QM, JH), pp. 957–966.
KDIRKDIR-2009-BalujaRS #classification #performance
Text Classification through Time — Efficient Label Propagation in Time-Based Graphs (SB, DR, DS), pp. 174–182.
KEODKEOD-2009-ThwaitesFS
Chain Event Graph Map Model Selection (PAT, GF, JQS), pp. 392–395.
MLDMMLDM-2009-RiesenB #difference #prototype #reduction #using
Dissimilarity Based Vector Space Embedding of Graphs Using Prototype Reduction Schemes (KR, HB), pp. 617–631.
SEKESEKE-2009-MajumdarB
Separating The Scattered Concerns: A Graph Based Model (DM, SB), pp. 715–720.
SEKESEKE-2009-RusNSC #algorithm #clustering #fault #using
Clustering of Defect Reports Using Graph Partitioning Algorithms (VR, XN, SGS, YC), pp. 442–445.
SEKESEKE-2009-SarkarCCB #concept #multi #specification
Object Specification Language for Graph Based Conceptual level Multidimensional Data Model (AS, SC, NC, SB), pp. 694–607.
SIGIRSIGIR-2009-DengKL #modelling #query #representation
Entropy-biased models for query representation on the click graph (HD, IK, MRL), pp. 339–346.
SIGIRSIGIR-2009-GuanBMCW #multi #personalisation #ranking #recommendation #using
Personalized tag recommendation using graph-based ranking on multi-type interrelated objects (ZG, JB, QM, CC, CW), pp. 540–547.
SIGIRSIGIR-2009-SakumaK #analysis
Link analysis for private weighted graphs (JS, SK), pp. 235–242.
SIGIRSIGIR-2009-SeoJ #precise #retrieval #using
High precision retrieval using relevance-flow graph (JS, JJ), pp. 694–695.
SIGIRSIGIR-2009-YeHL #approach #mining #multi #wiki #word
A graph-based approach to mining multilingual word associations from wikipedia (ZY, XH, HL), pp. 690–691.
OOPSLAOOPSLA-2009-PluquetLW #in memory #performance #version control
Executing code in the past: efficient in-memory object graph versioning (FP, SL, RW), pp. 391–408.
SASSAS-2009-WehrleH #model checking
The Causal Graph Revisited for Directed Model Checking (MW, MH), pp. 86–101.
ESEC-FSEESEC-FSE-2009-JeongKZ #debugging
Improving bug triage with bug tossing graphs (GJ, SK, TZ), pp. 111–120.
ESEC-FSEESEC-FSE-2009-NguyenNPAN #mining #multi
Graph-based mining of multiple object usage patterns (TTN, HAN, NHP, JMAK, TNN), pp. 383–392.
ICSEICSE-2009-PhamNNAN #clone detection #detection #modelling
Complete and accurate clone detection in graph-based models (NHP, HAN, TTN, JMAK, TNN), pp. 276–286.
SACSAC-2009-DungDH #constraints #framework #optimisation
LS(graph & tree): a local search framework for constraint optimization on graphs and trees (PQD, YD, PVH), pp. 1402–1407.
SACSAC-2009-GaoS #performance
Characterizing 1-dof Henneberg-I graphs with efficient configuration spaces (HG, MS), pp. 1122–1126.
SACSAC-2009-HendersonE #scalability
Applying latent dirichlet allocation to group discovery in large graphs (KH, TER), pp. 1456–1461.
SACSAC-2009-KumarZ #clustering #visualisation
Visualization of clustered directed acyclic graphs with node interleaving (PK, KZ), pp. 1800–1805.
CASECASE-2009-AlenljungL #using #verification
Formal verification of PLC controlled systems using Sensor Graphs (TA, BL), pp. 164–170.
DACDAC-2009-Falk
WCET-aware register allocation based on graph coloring (HF), pp. 726–731.
DACDAC-2009-Geilen #data flow #reduction
Reduction techniques for synchronous dataflow graphs (MG), pp. 911–916.
DACDAC-2009-JainC #performance #satisfiability #using
Efficient SAT solving for non-clausal formulas using DPLL, graphs, and watched cuts (HJ, EMC), pp. 563–568.
DACDAC-2009-WangCSC #power management #synthesis #using
Low power gated bus synthesis using shortest-path Steiner graph for system-on-chip communications (RW, NCC, BS, CKC), pp. 166–171.
DATEDATE-2009-Gomez-PradoRCGB #data flow #hardware #implementation #optimisation
Optimizing data flow graphs to minimize hardware implementation (DGP, QR, MJC, JG, EB), pp. 117–122.
HPDCHPDC-2009-QinFP #approach #automation #composition #grid #novel #quality #workflow
A novel graph based approach for automatic composition of high quality grid workflows (JQ, TF, RP), pp. 167–176.
HPDCHPDC-2009-SaballusF #distributed #maintenance
Maintaining reference graphs of globally accessible objects in fully decentralized distributed systems (BS, TF), pp. 59–60.
LCTESLCTES-2009-ZouABL #embedded #flexibility #realtime #theory and practice
PTIDES on flexible task graph: real-time embedded systembuilding from theory to practice (JZ, JSA, DFB, EAL), pp. 31–40.
PPoPPPPoPP-2009-KangB #algorithm #memory management #performance #transaction
An efficient transactional memory algorithm for computing minimum spanning forest of sparse graphs (SK, DAB), pp. 15–24.
PPoPPPPoPP-2009-YangWXDZ #optimisation
Comparability graph coloring for optimizing utilization of stream register files in stream processors (XY, LW, JX, YD, YZ), pp. 111–120.
SOSPSOSP-2009-DunaganZS #combinator #named #optimisation #using
Heat-ray: combating identity snowball attacks using machinelearning, combinatorial optimization and attack graphs (JD, AXZ, DRS), pp. 305–320.
FASEFASE-2009-HermannEE #inheritance #network #security
Transformation of Type Graphs with Inheritance for Ensuring Security in E-Government Networks (FH, HE, CE), pp. 325–339.
FoSSaCSFoSSaCS-2009-AntonopoulosD #logic
Separating Graph Logic from MSO (TA, AD), pp. 63–77.
STOCSTOC-2009-ChalopinG
Every planar graph is the intersection graph of segments in the plane: extended abstract (JC, DG), pp. 631–638.
STOCSTOC-2009-ChechikLPR #fault tolerance
Fault-tolerant spanners for general graphs (SC, ML, DP, LR), pp. 435–444.
STOCSTOC-2009-KolaitisK #quantifier #random
Random graphs and the parity quantifier (PGK, SK), pp. 705–714.
STOCSTOC-2009-LeeS #geometry #on the
On the geometry of graphs with a forbidden minor (JRL, AS), pp. 245–254.
CADECADE-2009-KorpM #dependence
Beyond Dependency Graphs (MK, AM), pp. 339–354.
ICSTICST-2009-GligoricGLMK #generative #java #optimisation
Optimizing Generation of Object Graphs in Java PathFinder (MG, TG, SL, DM, SK), pp. 51–60.
ISSTAISSTA-2009-ChengLZWY #debugging #identification #mining #using
Identifying bug signatures using discriminative graph mining (HC, DL, YZ, XW, XY), pp. 141–152.
LICSLICS-2009-Tan #automaton #infinity #reachability
Graph Reachability and Pebble Automata over Infinite Alphabets (TT), pp. 157–166.
MBTMBT-2009-SchumannSH #nondeterminism #testing #using
Computing Optimal Tests for Non-deterministic Systems Using DNNF Graphs (AS, MS, JH), pp. 87–99.
WICSAWICSA-2008-ChangMQ #architecture #configuration management #formal method #towards
Towards a Formal Model for Reconfigurable Software Architectures by Bigraphs (ZC, XM, ZQ), pp. 331–334.
DocEngDocEng-2008-Al-SaffarH #semantics
Semantic impact graphs for information valuation (SAS, GLH), pp. 209–212.
DRRDRR-2008-GacebELE #locality
Address block localization based on graph theory (DG, VE, FL, HE), p. 68150.
PODSPODS-2008-SarmaGP #rank
Estimating PageRank on graph streams (ADS, SG, RP), pp. 69–78.
SIGMODSIGMOD-2008-BollackerEPST #database #named
Freebase: a collaboratively created graph database for structuring human knowledge (KDB, CE, PP, TS, JT), pp. 1247–1250.
SIGMODSIGMOD-2008-GolenbergKS #keyword #proximity
Keyword proximity search in complex data graphs (KG, BK, YS), pp. 927–940.
SIGMODSIGMOD-2008-GouC #algorithm #pattern matching #performance
Efficient algorithms for exact ranked twig-pattern matching over graphs (GG, RC), pp. 581–594.
SIGMODSIGMOD-2008-HeS #data access #database #named #query
Graphs-at-a-time: query language and access methods for graph databases (HH, AKS), pp. 405–418.
SIGMODSIGMOD-2008-JinXRW #query #reachability #scalability
Efficiently answering reachability queries on very large directed graphs (RJ, YX, NR, HW), pp. 595–608.
SIGMODSIGMOD-2008-LiuT #towards
Towards identity anonymization on graphs (KL, ET), pp. 93–106.
SIGMODSIGMOD-2008-NavlakhaRS #bound #fault #summary
Graph summarization with bounded error (SN, RR, NS), pp. 419–432.
SIGMODSIGMOD-2008-TianHP #performance #summary
Efficient aggregation for graph summarization (YT, RAH, JMP), pp. 567–580.
SIGMODSIGMOD-2008-VuOPT #database #keyword
A graph method for keyword-based selection of the top-K databases (QHV, BCO, DP, AKHT), pp. 915–926.
SIGMODSIGMOD-2008-YanCHY #mining
Mining significant graph patterns by leap search (XY, HC, JH, PSY), pp. 433–444.
VLDBVLDB-2008-AntonellisGC #analysis #query
Simrank++: query rewriting through link analysis of the click graph (IA, HGM, CCC), pp. 408–421.
VLDBVLDB-2008-CormodeSYZ #using
Anonymizing bipartite graph data using safe groupings (GC, DS, TY, QZ), pp. 833–844.
VLDBVLDB-2008-DalviKS #keyword #memory management
Keyword search on external memory data graphs (BBD, MK, SS), pp. 1189–1204.
VLDBVLDB-2008-TianPNMK #named #query #tool support
Periscope/GQ: a graph querying toolkit (YT, JMP, VN, SM, MK), pp. 1404–1407.
EDMEDM-2008-LynchAPA #classification #programming #search-based
Argument graph classification with Genetic Programming and C4.5 (CL, KDA, NP, VA), pp. 137–146.
ICPCICPC-2008-Quante #comprehension #empirical #process
Do Dynamic Object Process Graphs Support Program Understanding? — A Controlled Experiment (JQ), pp. 73–82.
ICSMEICSM-2008-LinZKM #editing #visualisation
A domain-customizable SVG-based graph editor for software visualizations (TL, FZ, HMK, HAM), pp. 466–467.
SCAMSCAM-2008-GermanRH #impact analysis
Change Impact Graphs: Determining the Impact of Prior Code Changes (DMG, GR, AEH), pp. 184–193.
SCAMSCAM-2008-ScholzZC #analysis #dependence #reachability
User-Input Dependence Analysis via Graph Reachability (BS, CZ, CC), pp. 25–34.
WCREWCRE-2008-KpodjedoRGA #evolution #fault
Error Correcting Graph Matching Application to Software Evolution (SK, FR, PG, GA), pp. 289–293.
AFLAFL-2008-KuskeL #automation #recursion
Euler paths and ends in automatic and recursive graphs (DK, ML), pp. 245–256.
ICALPICALP-A-2008-AvinKL #evolution #how #random
How to Explore a Fast-Changing World (Cover Time of a Simple Random Walk on Evolving Graphs) (CA, MK, ZL), pp. 121–132.
ICALPICALP-A-2008-BaswanaGSU #constant #distance #fault #polynomial
Distance Oracles for Unweighted Graphs: Breaking the Quadratic Barrier with Constant Additive Error (SB, AG, SS, JU), pp. 609–621.
ICALPICALP-A-2008-BjorklundHKK #bound #problem
The Travelling Salesman Problem in Bounded Degree Graphs (AB, TH, PK, MK), pp. 198–209.
ICALPICALP-A-2008-BlellochVW #approach #combinator #problem
A New Combinatorial Approach for Sparse Graph Problems (GEB, VV, RW), pp. 108–120.
ICALPICALP-A-2008-BorradaileK #network #problem
The Two-Edge Connectivity Survivable Network Problem in Planar Graphs (GB, PNK), pp. 485–501.
ICALPICALP-A-2008-CheboluFM #random
Finding a Maximum Matching in a Sparse Random Graph in O(n) Expected Time (PC, AMF, PM), pp. 161–172.
ICALPICALP-A-2008-ChierichettiV
The Local Nature of List Colorings for Graphs of High Girth (FC, AV), pp. 320–332.
ICALPICALP-A-2008-Courcelle #aspect-oriented #higher-order #logic #monad
Graph Structure and Monadic Second-Order Logic: Language Theoretical Aspects (BC), pp. 1–13.
ICALPICALP-A-2008-DraganFG
Spanners in Sparse Graphs (FFD, FVF, PAG), pp. 597–608.
ICALPICALP-A-2008-KaleS #bound
An Expansion Tester for Bounded Degree Graphs (SK, CS), pp. 527–538.
ICALPICALP-A-2008-YoshidaI #testing
Property Testing on k-Vertex-Connectivity of Graphs (YY, HI), pp. 539–550.
LATALATA-2008-BrijderH #assembly
Extending the Overlap Graph for Gene Assembly in Ciliates (RB, HJH), pp. 137–148.
RTARTA-2008-MazanekM #combinator #functional #parsing
Functional-Logic Graph Parser Combinators (SM, MM), pp. 261–275.
ICFPICFP-2008-AdamsD #performance #similarity
Efficient nondestructive equality checking for trees and graphs (MDA, RKD), pp. 179–188.
GT-VMTGT-VMT-2008-AzabP #c++ #source code #type checking
Type Checking C++ Template Instantiation by Graph Programs (KA, KHP).
GT-VMTGT-VMT-2008-GrohmannM #resource management
Controlling resource access in Directed Bigraphs (DG, MM).
GT-VMTGT-VMT-2008-MazanekM #combinator #parsing
Parsing of Hyperedge Replacement Grammars with Graph Parser Combinators (SM, MM).
GT-VMTGT-VMT-2008-RensinkK #diagrams #on the #semantics #uml
On a Graph-Based Semantics for UML Class and Object Diagrams (AR, AK).
GT-VMTGT-VMT-2008-Weinell #query #reduction
Extending Graph Query Languages by Reduction (EW).
GT-VMTGT-VMT-2008-Xing #representation
A Graph-Based Type Representation for Objects (CCX).
ICGTICGT-2008-BauerBKR #abstraction
A Modal-Logic Based Graph Abstraction (JB, IB, MEK, AR), pp. 321–335.
ICGTICGT-2008-BrugginkK #on the
On the Recognizability of Arrow and Graph Languages (HJSB, BK), pp. 336–350.
ICGTICGT-2008-CenciarelliGT #bisimulation #network
Network Applications of Graph Bisimulation (PC, DG, ET), pp. 131–146.
ICGTICGT-2008-ChalopinMM #problem
Labelled (Hyper)Graphs, Negotiations and the Naming Problem (JC, AWM, YM), pp. 54–68.
ICGTICGT-2008-DerbelMG #implementation #mobile
Mobile Agents Implementing Local Computations in Graphs (BD, MM, SG), pp. 99–114.
ICGTICGT-2008-DrewesHM #adaptation #modelling
Adaptive Star Grammars for Graph Models (FD, BH, MM), pp. 442–457.
ICGTICGT-2008-EhrigE #correctness #model transformation #semantics #using
Semantical Correctness and Completeness of Model Transformations Using Graph and Rule Transformation (HE, CE), pp. 194–210.
ICGTICGT-2008-EhrigP #analysis #formal method #kernel #model transformation
Formal Analysis of Model Transformations Based on Triple Graph Rules with Kernels (HE, UP), pp. 178–193.
ICGTICGT-2008-Grohmann #encryption #security
Security, Cryptography and Directed Bigraphs (DG), pp. 487–489.
ICGTICGT-2008-JelinkovaK #on the
On Switching to H-Free Graphs (EJ, JK), pp. 379–395.
ICGTICGT-2008-KreowskiK #framework #parallel
Graph Multiset Transformation as a Framework for Massively Parallel Computation (HJK, SK), pp. 351–365.
ICGTICGT-2008-Orejas #constraints
Attributed Graph Constraints (FO), pp. 274–288.
ICGTICGT-2008-RensinkG #contest #tool support
Graph-Based Tools: The Contest (AR, PVG), pp. 463–466.
ICGTICGT-2008-Weinell
Transformation-Based Operationalization of Graph Languages (EW), pp. 520–522.
SOFTVISSOFTVIS-2008-DietrichYMJD #analysis #clustering #dependence #java
Cluster analysis of Java dependency graphs (JD, VY, CM, GJ, MD), pp. 91–94.
SOFTVISSOFTVIS-2008-ParduhnSW #algorithm #using #visualisation
Algorithm visualization using concrete and abstract shape graphs (SAP, RS, RW), pp. 33–36.
SOFTVISSOFTVIS-2008-PichNR #analysis #dependence #visual notation
Visual analysis of importance and grouping in software dependency graphs (CP, LN, GGR), pp. 29–32.
SOFTVISSOFTVIS-2008-ZeckzerKSHK #3d #clustering #communication #reliability #using #visualisation
Analyzing the reliability of communication between software entities using a 3D visualization of clustered graphs (DZ, RK, LS, HH, TK), pp. 37–46.
EDOCEDOC-2008-SommestadEJ #analysis #architecture #enterprise #modelling #security
Combining Defense Graphs and Enterprise Architecture Models for Security Analysis (TS, ME, PJ), pp. 349–355.
ICEISICEIS-ISAS2-2008-BainaT #algorithm #hybrid #towards #verification #workflow
Toward a Hybrid Algorithm for Workflow Graph Structural Verification (FT, KB, WG), pp. 442–447.
CIKMCIKM-2008-BoldiBCDGV
The query-flow graph: model and applications (PB, FB, CC, DD, AG, SV), pp. 609–618.
CIKMCIKM-2008-ChenLYH #approach #effectiveness #on the
On effective presentation of graph patterns: a structural representative approach (CC, CXL, XY, JH), pp. 299–308.
CIKMCIKM-2008-DaoudTB #ontology #personalisation #using
Using a graph-based ontological user profile for personalizing search (MD, LTL, MB), pp. 1495–1496.
CIKMCIKM-2008-FanWLZH #effectiveness #framework #named
GHOST: an effective graph-based framework for name distinction (XF, JW, BL, LZ, WH), pp. 1449–1450.
CIKMCIKM-2008-FeiH #classification #feature model
Structure feature selection for graph classification (HF, JH), pp. 991–1000.
CIKMCIKM-2008-HerschelN #detection #scalability
Scaling up duplicate detection in graph data (MH, FN), pp. 1325–1326.
CIKMCIKM-2008-Ibekwe-SanjuanSV #composition #information management
Decomposition of terminology graphs for domain knowledge acquisition (FIS, ES, MSEV), pp. 1463–1464.
CIKMCIKM-2008-ModaniD #clique #scalability
Large maximal cliques enumeration in sparse graphs (NM, KD), pp. 1377–1378.
CIKMCIKM-2008-PobleteCG
Dr. Searcher and Mr. Browser: a unified hyperlink-click graph (BP, CC, AG), pp. 1123–1132.
ECIRECIR-2008-HannahMO #analysis
Analysis of Link Graph Compression Techniques (DH, CM, IO), pp. 596–601.
ECIRECIR-2008-NaderiR #evaluation #similarity
Graph-Based Profile Similarity Calculation Method and Evaluation (HN, BR), pp. 637–641.
ECIRECIR-2008-StathopoulosUJ #automation #image #multi #semantics
Semantic Relationships in Multi-modal Graphs for Automatic Image Annotation (VS, JU, JMJ), pp. 490–497.
ECIRECIR-2008-ValletHJ #evaluation #recommendation #using
Use of Implicit Graph for Recommending Relevant Videos: A Simulated Evaluation (DV, FH, JMJ), pp. 199–210.
ECIRECIR-2008-WeiLLH #clustering #multi #query #summary
A Cluster-Sensitive Graph Model for Query-Oriented Multi-document Summarization (FW, WL, QL, YH), pp. 446–453.
ICMLICML-2008-Bach #kernel
Graph kernels between point clouds (FRB), pp. 25–32.
ICMLICML-2008-KondorB
The skew spectrum of graphs (RK, KMB), pp. 496–503.
ICMLICML-2008-SarkarMP #incremental #performance #proximity #scalability
Fast incremental proximity search in large graphs (PS, AWM, AP), pp. 896–903.
ICMLICML-2008-WangJC
Graph transduction via alternating minimization (JW, TJ, SFC), pp. 1144–1151.
ICPRICPR-2008-EmmsHW #quantum #using
Graph drawing using quantum commute time (DE, ERH, RCW), pp. 1–4.
ICPRICPR-2008-FerrerVSRB #algorithm #approximate #using
An approximate algorithm for median graph computation using graph embedding (MF, EV, FS, KR, HB), pp. 1–4.
ICPRICPR-2008-FundanaHGS #segmentation
Continuous graph cuts for prior-based object segmentation (KF, AH, CG, CS), pp. 1–4.
ICPRICPR-2008-GhoniemCE #video
Video denoising via discrete regularization on graphs (MG, YC, AE), pp. 1–4.
ICPRICPR-2008-GongC #learning #online #optimisation #realtime #segmentation #using
Real-time foreground segmentation on GPUs using local online learning and global graph cut optimization (MG, LC), pp. 1–4.
ICPRICPR-2008-Gonzalez-AguirreABD #geometry #modelling #self #using #visual notation
Model-based visual self-localization using geometry and graphs (DIGA, TA, EBC, RD), pp. 1–5.
ICPRICPR-2008-GuimaraesPP #approach #detection #difference #distance #using #video
An approach for video cut detection using bipartite graph matching as dissimilarity distance (SJFG, ZKGdPJ, HBdP), pp. 1–4.
ICPRICPR-2008-KokiopoulouPF #classification #multi
Graph-based classification for multiple observations of transformed patterns (EK, SP, PF), pp. 1–4.
ICPRICPR-2008-LebrunPG #image #kernel #retrieval
Image retrieval with graph kernel on regions (JL, SPF, PHG), pp. 1–4.
ICPRICPR-2008-LeKM #clustering
Coring method for clustering a graph (TVL, CAK, IBM), pp. 1–4.
ICPRICPR-2008-LezorayTE #clustering
Impulse noise removal by spectral clustering and regularization on graphs (OL, VTT, AE), pp. 1–4.
ICPRICPR-2008-LezorayTE08a #image
Nonlocal graph regularization for image colorization (OL, VTT, AE), pp. 1–4.
ICPRICPR-2008-LiuLLJT #probability #representation
Layered shape matching and registration: Stochastic sampling with hierarchical graph representation (XL, LL, HL, HJ, WT), pp. 1–4.
ICPRICPR-2008-RothausJ #clustering #distance #novel
Constrained clustering by a novel graph-based distance transformation (KR, XJ), pp. 1–4.
ICPRICPR-2008-SanromaSA #clique #using
Improving the matching of graphs generated from shapes by the use of procrustes distances into a clique-based MAP formulation (GS, FS, RA), pp. 1–4.
ICPRICPR-2008-ShiS #recognition
A symbol graph based handwritten math expression recognition (YS, FKS), pp. 1–4.
ICPRICPR-2008-SugaFTA #recognition #segmentation #using
Object recognition and segmentation using SIFT and Graph Cuts (AS, KF, TT, YA), pp. 1–4.
ICPRICPR-2008-TaEL #difference #equation
Nonlocal morphological levelings by partial difference equations over weighted graphs (VTT, AE, OL), pp. 1–4.
ICPRICPR-2008-TangG #constraints #segmentation #video
Video object segmentation based on graph cut with dynamic shape prior constraint (PT, LG), pp. 1–4.
ICPRICPR-2008-TorselloD #generative #learning
Supervised learning of a generative model for edge-weighted graphs (AT, DLD), pp. 1–4.
ICPRICPR-2008-WhiteW #generative #modelling
Parts based generative models for graphs (DHW, RCW), pp. 1–4.
ICPRICPR-2008-XiaoWH #invariant #recognition #using
Object recognition using graph spectral invariants (XB, RCW, ERH), pp. 1–4.
ICPRICPR-2008-ZitouniSOD #algorithm #image #ranking #using #web
Re-ranking of web image search results using a graph algorithm (HZ, SGS, DO, PD), pp. 1–4.
KDDKDD-2008-BecchettiBCG #algorithm #performance
Efficient semi-streaming algorithms for local triangle counting in massive graphs (LB, PB, CC, AG), pp. 16–24.
KDDKDD-2008-HwangKRZ #mining
Bridging centrality: graph mining from element level to group level (WH, TK, MR, AZ), pp. 336–344.
KDDKDD-2008-McGlohonAF #component #generative
Weighted graphs and disconnected components: patterns and a generator (MM, LA, CF), pp. 524–532.
KDDKDD-2008-SaigoKT #mining
Partial least squares regression for graph mining (HS, NK, KT), pp. 578–586.
KDDKDD-2008-SatoYN #information management #parametricity #semantics #using #word
Knowledge discovery of semantic relationships between words using nonparametric bayesian graph model (IS, MY, HN), pp. 587–595.
KDDKDD-2008-SeshadriMSBFL #mobile
Mobile call graphs: beyond power-law and lognormal distributions (MS, SM, AS, JB, CF, JL), pp. 596–604.
KDDKDD-2008-TongPSYF #mining #named #performance #scalability
Colibri: fast mining of large static and dynamic graphs (HT, SP, JS, PSY, CF), pp. 686–694.
KDDKDD-2008-YangAPM #interactive #tool support
A visual-analytic toolkit for dynamic interaction graphs (XY, SA, SP, SM), pp. 1016–1024.
KRKR-2008-MotikGHS #representation #using
Representing Structured Objects using Description Graphs (BM, BCG, IH, US), pp. 296–306.
KRKR-2008-Rintanen
Planning Graphs and Propositional Clause-Learning (JR), pp. 535–543.
RecSysRecSys-2008-HadzicO #navigation
Critique graphs for catalogue navigation (TH, BO), pp. 115–122.
SEKESEKE-2008-KraftW #eclipse
Evaluating the Accuracy of Call Graphs Extracted with the Eclipse CDT (NAK, KSW), pp. 85–90.
SIGIRSIGIR-2008-BenderskyK #ranking #using
Re-ranking search results using document-passage graphs (MB, OK), pp. 853–854.
SIGIRSIGIR-2008-LiWA #learning #query
Learning query intent from regularized click graphs (XL, YYW, AA), pp. 339–346.
SIGIRSIGIR-2008-MeiZZ #framework #modelling #optimisation
A general optimization framework for smoothing language models on graph structures (QM, DZ, CZ), pp. 611–618.
PLDIPLDI-2008-HackG
Copy coalescing by graph recoloring (SH, GG), pp. 227–237.
ICSEICSE-2008-ZimmermannN #analysis #dependence #fault #network #predict #using
Predicting defects using network analysis on dependency graphs (TZ, NN), pp. 531–540.
SACSAC-2008-AbedMS #analysis #multi #proving #reachability #theorem proving #using
Reachability analysis using multiway decision graphs in the HOL theorem prover (SA, OAM, GAS), pp. 333–338.
SACSAC-2008-BaF #composition #dependence #web #web service
Dependence graphs for verifications of web service compositions with PEWS (CB, MHF), pp. 2387–2391.
SACSAC-2008-BussBSE #analysis #flexibility #pointer #using
Flexible pointer analysis using assign-fetch graphs (MB, DB, VCS, SAE), pp. 234–239.
SACSAC-2008-NaderiRP #collaboration #information retrieval #similarity
A graph-based profile similarity calculation method for collaborative information retrieval (HN, BR, JMP), pp. 1127–1131.
SACSAC-2008-RamanathanKGJ #framework #named #testing
PHALANX: a graph-theoretic framework for test case prioritization (MKR, MK, AG, SJ), pp. 667–673.
SACSAC-2008-ZhouTBAG #ambiguity #named #query
Gcon: a graph-based technique for resolving ambiguity in query translation candidates (DZ, MT, TJB, HA, JG), pp. 1566–1573.
CASECASE-2008-AddadA #algebra #architecture #evaluation #modelling #using
Modeling and response time evaluation of ethernet-based control architectures using timed event graphs and Max-Plus algebra (BA, SA), pp. 418–423.
CASECASE-2008-Balasundaram #mining
Cohesive subgroup model for graph-based text mining (BB), pp. 989–994.
CCCC-2008-MarronHKS #analysis #modelling #performance
Efficient Context-Sensitive Shape Analysis with Graph Based Heap Models (MM, MVH, DK, DS), pp. 245–259.
CCCC-2008-WurthingerWM #dependence #visualisation
Visualization of Program Dependence Graphs (TW, CW, HM), pp. 193–196.
CGOCGO-2008-KoesG
Near-optimal instruction selection on dags (DRK, SCG), pp. 45–54.
DACDAC-2008-HsuPB #data flow #parallel #simulation #thread
Multithreaded simulation for synchronous dataflow graphs (CJH, JLP, SSB), pp. 331–336.
DATEDATE-2008-GhamarianGBS #analysis #data flow #parametricity #throughput
Parametric Throughput Analysis of Synchronous Data Flow Graphs (AHG, MG, TB, SS), pp. 116–121.
DATEDATE-2008-HosseinabadyKMP #architecture #energy #latency #performance #scalability
De Bruijn Graph as a Low Latency Scalable Architecture for Energy Efficient Massive NoCs (MH, MRK, JM, DKP), pp. 1370–1373.
DATEDATE-2008-MokhovY #configuration management #partial order #synthesis
Conditional Partial Order Graphs and Dynamically Reconfigurable Control Synthesis (AM, AY), pp. 1142–1147.
HPCAHPCA-2008-ChenMP #constraints #memory management #runtime #using #validation
Runtime validation of memory ordering using constraint graph checking (KC, SM, PP), pp. 415–426.
LCTESLCTES-2008-AuerbachBGSV #concurrent #flexibility #java #programming #strict #thread
Flexible task graphs: a unified restricted thread programming model for java (JSA, DFB, RG, JHS, JV), pp. 1–11.
PDPPDP-2008-LinC #algorithm #clustering #internet #named #parallel #simulation
BC-GA: A Graph Partitioning Algorithm for Parallel Simulation of Internet Applications (SL, XC), pp. 358–365.
FASEFASE-2008-OrejasEP #constraints #logic
A Logic of Graph Constraints (FO, HE, UP), pp. 179–198.
STOCSTOC-2008-AroraKKSTV #constraints #game studies
Unique games on expanding constraint graphs are easy: extended abstract (SA, SK, AK, DS, MT, NKV), pp. 21–28.
STOCSTOC-2008-BartoKN #complexity #morphism #problem
Graphs, polymorphisms and the complexity of homomorphism problems (LB, MK, TN), pp. 789–796.
STOCSTOC-2008-Ben-AroyaT #combinator #using
A combinatorial construction of almost-ramanujan graphs using the zig-zag product (ABA, ATS), pp. 325–334.
STOCSTOC-2008-BenjaminiSS
Every minor-closed property of sparse graphs is testable (IB, OS, AS), pp. 393–402.
STOCSTOC-2008-ChoiK #bound #complexity #query
Optimal query complexity bounds for finding graphs (SSC, JHK), pp. 749–758.
STOCSTOC-2008-FriezeVV #random
Logconcave random graphs (AMF, SV, JV), pp. 779–788.
STOCSTOC-2008-KawarabayashiM #linear #morphism
Graph and map isomorphism and all polyhedral embeddings in linear time (KiK, BM), pp. 471–480.
STOCSTOC-2008-OrecchiaSVV #clustering #on the
On partitioning graphs via single commodity flows (LO, LJS, UVV, NKV), pp. 461–470.
STOCSTOC-2008-SpielmanS #effectiveness
Graph sparsification by effective resistances (DAS, NS), pp. 563–568.
ISSTAISSTA-2008-BaahPH #dependence #fault #probability
The probabilistic program dependence graph and its application to fault diagnosis (GKB, AP, MJH), pp. 189–200.
TPDLECDL-2007-WanX #approach #multi #towards
Towards a Unified Approach Based on Affinity Graph to Various Multi-document Summarizations (XW, JX), pp. 297–308.
SIGMODSIGMOD-2007-ChengKNL #database #named #query #towards
Fg-index: towards verification-free query processing on graph databases (JC, YK, WN, AL), pp. 857–872.
SIGMODSIGMOD-2007-FaloutsosKS #matrix #mining #scalability #tool support #using
Mining large graphs and streams using matrix and tensor tools (CF, TGK, JS), p. 1174.
SIGMODSIGMOD-2007-HeWYY #keyword #named
BLINKS: ranked keyword searches on graphs (HH, HW, JY, PSY), pp. 305–316.
SIGMODSIGMOD-2007-TrisslL #performance #query #scalability
Fast and practical indexing and querying of very large graphs (ST, UL), pp. 845–856.
VLDBVLDB-2007-ChenYYHZG #towards
Towards Graph Containment Search and Indexing (CC, XY, PSY, JH, DQZ, XG), pp. 926–937.
VLDBVLDB-2007-QiCS #query
Sum-Max Monotonic Ranked Joins for Evaluating Top-K Twig Queries on Weighted Data Graphs (YQ, KSC, MLS), pp. 507–518.
VLDBVLDB-2007-ZhaoYY
Graph Indexing: Tree + Delta >= Graph (PZ, JXY, PSY), pp. 938–949.
ITiCSEITiCSE-2007-Sanchez-TorrubiaTC #algorithm #interactive #learning #tool support
New interactive tools for graph algorithms active learning (MGST, CTB, JC), p. 337.
CSMRCSMR-2007-Quante #online #process
Online Construction of Dynamic Object Process Graphs (JQ), pp. 113–122.
CSMRCSMR-2007-Quante07a #comprehension #process #protocol
Dynamic Object Process Graph Extraction for Program Understanding and Protocol Recovery (JQ), pp. 345–348.
ICSMEICSM-2007-BernardiL #aspect-oriented #control flow #interprocedural #maintenance
An Interprocedural Aspect Control Flow Graph to Support the Maintenance of Aspect Oriented Systems (MLB, GADL), pp. 435–444.
PASTEPASTE-2007-Lhotak
Comparing call graphs (OL), pp. 37–42.
SCAMSCAM-2007-LochbihlerS #dependence #on the
On Temporal Path Conditions in Dependence Graphs (AL, GS), pp. 49–58.
DLTDLT-2007-BrijderH #assembly #reduction
Characterizing Reduction Graphs for Gene Assembly in Ciliates (RB, HJH), pp. 120–131.
DLTDLT-2007-Priese #automaton #finite
Finite Automata on Unranked and Unordered DAGs (LP), pp. 346–360.
ICALPICALP-2007-AlonCHKRS #algorithm
Quasi-randomness and Algorithmic Regularity for Graphs with General Degree Distributions (NA, ACO, HH, MK, VR, MS), pp. 789–800.
ICALP