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113 papers:

VLDBVLDB-2015-GalhotraBBRJ #evolution #topic
Tracking the Conductance of Rapidly Evolving Topic-Subgraphs (SG, AB, SB, MR, VJ), pp. 2170–2181.
VLDBVLDB-2015-KatsarouNT #performance #query #scalability
Performance and Scalability of Indexed Subgraph Query Processing Methods (FK, NN, PT), pp. 1566–1577.
VLDBVLDB-2015-KimSHHC #morphism #query #rdf
Taming Subgraph Isomorphism for RDF Query Processing (JK, HS, WSH, SH, HC), pp. 1238–1249.
VLDBVLDB-2015-LaiQLC #pipes and filters #scalability
Scalable Subgraph Enumeration in MapReduce (LL, LQ, XL, LC), pp. 974–985.
VLDBVLDB-2015-RenW #graph #morphism #scalability
Exploiting Vertex Relationships in Speeding up Subgraph Isomorphism over Large Graphs (XR, JW), pp. 617–628.
STOCSTOC-2015-Barman #approximate #nash #theorem
Approximating Nash Equilibria and Dense Bipartite Subgraphs via an Approximate Version of Caratheodory’s Theorem (SB), pp. 361–369.
STOCSTOC-2015-BhattacharyaHNT #algorithm #maintenance
Space- and Time-Efficient Algorithm for Maintaining Dense Subgraphs on One-Pass Dynamic Streams (SB, MH, DN, CET), pp. 173–182.
KDDKDD-2015-GionisT #tutorial
Dense Subgraph Discovery: KDD 2015 tutorial (AG, CET), pp. 2313–2314.
KDDKDD-2015-QinLCZ
Locally Densest Subgraph Discovery (LQ, RHL, LC, CZ), pp. 965–974.
SIGMODSIGMOD-2014-AroraSB #graph #mining #statistics
Mining statistically significant connected subgraphs in vertex labeled graphs (AA, MS, AB), pp. 1003–1014.
SIGMODSIGMOD-2014-ShaoCC #detection #parallel #performance
Efficient cohesive subgraphs detection in parallel (YS, LC, BC), pp. 613–624.
SIGMODSIGMOD-2014-ShaoCCMYX #graph #parallel #scalability
Parallel subgraph listing in a large-scale graph (YS, BC, LC, LM, JY, NX), pp. 625–636.
VLDBVLDB-2014-ElseidyASK #graph #mining #named #scalability
GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph (ME, EA, SS, PK), pp. 517–528.
ICGTICGT-2014-RidderR #morphism #problem
The Subgraph Isomorphism Problem on a Class of Hyperedge Replacement Languages (HNdR, NdR), pp. 192–206.
CIKMCIKM-2014-LiuXD #mining #network #predict
Relationship Emergence Prediction in Heterogeneous Networks through Dynamic Frequent Subgraph Mining (YL, SX, LD), pp. 1649–1658.
CIKMCIKM-2014-ZhengZLHZ #graph #performance #scalability
Efficient Subgraph Skyline Search Over Large Graphs (WZ, LZ, XL, LH, DZ), pp. 1529–1538.
ICMLICML-c2-2014-PapailiopoulosMDC #optimisation #rank
Finding Dense Subgraphs via Low-Rank Bilinear Optimization (DSP, IM, AGD, CC), pp. 1890–1898.
LICSLICS-CSL-2014-KreutzerS #on the
On Hanf-equivalence and the number of embeddings of small induced subgraphs (SK, NS), p. 10.
PODSPODS-2013-KimelfeldK #complexity #mining
The complexity of mining maximal frequent subgraphs (BK, PGK), pp. 13–24.
SIGMODSIGMOD-2013-HanLL #database #graph #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-HungBTCZ #named #network #query #scalability #visual notation
QUBLE: blending visual subgraph query formulation with query processing on large networks (HHH, SSB, BQT, BC, SZ), pp. 1097–1100.
ICALPICALP-v1-2013-AbboudL
Exact Weight Subgraphs and the k-Sum Conjecture (AA, KL), pp. 1–12.
CIKMCIKM-2013-AkibaIY #linear #network #random #scalability
Linear-time enumeration of maximal K-edge-connected subgraphs in large networks by random contraction (TA, YI, YY), pp. 909–918.
KDDKDD-2013-RanuHS #mining #network
Mining discriminative subgraphs from global-state networks (SR, MXH, AKS), pp. 509–517.
KDDKDD-2013-TsourakakisBGGT #clique #quality
Denser than the densest subgraph: extracting optimal quasi-cliques with quality guarantees (CET, FB, AG, FG, MAT), pp. 104–112.
PODSPODS-2012-AhnGM #graph #sketching
Graph sketches: sparsification, spanners, and subgraphs (KJA, SG, AM), pp. 5–14.
VLDBVLDB-2012-AngelKSS #identification #maintenance #realtime #streaming
Dense Subgraph Maintenance under Streaming Edge Weight Updates for Real-time Story Identification (AA, NK, NS, DS), pp. 574–585.
VLDBVLDB-2012-BahmaniKV #pipes and filters #streaming
Densest Subgraph in Streaming and MapReduce (BB, RK, SV), pp. 454–465.
VLDBVLDB-2012-SunWWSL #graph #performance
Efficient Subgraph Matching on Billion Node Graphs (ZS, HW, HW, BS, JL), pp. 788–799.
VLDBVLDB-2012-YuanWCW #database #graph #performance #probability #scalability #similarity
Efficient Subgraph Similarity Search on Large Probabilistic Graph Databases (YY, GW, LC, HW), pp. 800–811.
VLDBVLDB-2013-LeeHKL12 #algorithm #comparison #database #graph #morphism
An In-depth Comparison of Subgraph Isomorphism Algorithms in Graph Databases (JL, WSH, RK, JHL), pp. 133–144.
VLDBVLDB-2013-ZhaoT12 #analysis #network #scalability #social #visual notation
Large Scale Cohesive Subgraphs Discovery for Social Network Visual Analysis (FZ, AKHT), pp. 85–96.
STOCSTOC-2012-GroheM #graph #morphism #theorem
Structure theorem and isomorphism test for graphs with excluded topological subgraphs (MG, DM), pp. 173–192.
ICALPICALP-v1-2012-LaekhanukitGS #approach #problem
A Rounding by Sampling Approach to the Minimum Size k-Arc Connected Subgraph Problem (BL, SOG, MS), pp. 606–616.
ICALPICALP-v1-2012-LinC #complexity
The Parameterized Complexity of k-Edge Induced Subgraphs (BL, YC), pp. 641–652.
ICALPICALP-v2-2012-KaneMSS #data type
Counting Arbitrary Subgraphs in Data Streams (DMK, KM, TS, HS), pp. 598–609.
CIKMCIKM-2012-LinXCB #algorithm #performance #query
Efficient algorithms for generalized subgraph query processing (WL, XX, JC, SSB), pp. 325–334.
ICMLICML-2012-KriegeM #graph #kernel
Subgraph Matching Kernels for Attributed Graphs (NK, PM), p. 42.
ICPRICPR-2012-DahmBCG #detection #morphism
Topological features and iterative node elimination for speeding up subgraph isomorphism detection (ND, HB, TC, YG), pp. 1164–1167.
ICPRICPR-2012-PanZF #correlation #data type #query
Top-k correlated subgraph query for data streams (SP, XZ, MF), pp. 2906–2909.
KDDKDD-2012-BodenGHS #graph #mining #multi
Mining coherent subgraphs in multi-layer graphs with edge labels (BB, SG, HH, TS), pp. 1258–1266.
SIGIRSIGIR-2012-BonchiPSVV #performance #query #recommendation
Efficient query recommendations in the long tail via center-piece subgraphs (FB, RP, FS, HV, RV), pp. 345–354.
SACSAC-2012-SeelandBKP
Maximum Common Subgraph based locally weighted regression (MS, FB, SK, BP), pp. 165–172.
FSEFSE-2012-ChanCL #api
Searching connected API subgraph via text phrases (WKC, HC, DL), p. 10.
ICDARICDAR-2011-LuqmanRLB #documentation #graph #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-Saund #approach #graph #image #maintenance
A Graph Lattice Approach to Maintaining Dense Collections of Subgraphs as Image Features (ES), pp. 1069–1074.
SIGMODSIGMOD-2011-JinBXCZ #named #query #visual notation
GBLENDER: visual subgraph query formulation meets query processing (CJ, SSB, XX, BC, SZ), pp. 1327–1330.
VLDBVLDB-2011-YuanWWC #graph #nondeterminism #performance #scalability
Efficient Subgraph Search over Large Uncertain Graphs (YY, GW, HW, LC), pp. 876–886.
VLDBVLDB-2011-ZouMCOZ #named #query
gStore: Answering SPARQL Queries via Subgraph Matching (LZ, JM, LC, MTÖ, DZ), pp. 482–493.
STOCSTOC-2011-GroheKMW #parametricity
Finding topological subgraphs is fixed-parameter tractable (MG, KiK, DM, PW), pp. 479–488.
DLTDLT-2011-RodaroS #automaton #problem
Never Minimal Automata and the Rainbow Bipartite Subgraph Problem (ER, PVS), pp. 374–385.
LATALATA-2011-BrijderB
Characterizing Compressibility of Disjoint Subgraphs with NLC Grammars (RB, HB), pp. 167–178.
LATALATA-2011-KowalukLL
Unique Small Subgraphs Are Not Easier to Find (MK, AL, EML), pp. 336–341.
CIKMCIKM-2011-ChenWLXY #framework #named
SISP: a new framework for searching the informative subgraph based on PSO (CC, GW, HL, JX, YY), pp. 453–462.
CIKMCIKM-2011-WesselOVBK #3d #modelling #performance #retrieval #using
Efficient retrieval of 3D building models using embeddings of attributed subgraphs (RW, SO, RV, IB, RK), pp. 2097–2100.
ICMLICML-2011-VattaniCG #personalisation #rank
Preserving Personalized Pagerank in Subgraphs (AV, DC, MG), pp. 793–800.
KDDKDD-2011-JinLA #graph #nondeterminism #reliability
Discovering highly reliable subgraphs in uncertain graphs (RJ, LL, CCA), pp. 992–1000.
SEKESEKE-2011-VilkomirKT #algorithm #case study #interface #testing #using
Interface Testing Using a Subgraph Splitting Algorithm: A Case Study (SV, AAK, NT), pp. 219–224.
SACSAC-2011-Jamil #graph #query #unification #using
Computing subgraph isomorphic queries using structural unification and minimum graph structures (HMJ), pp. 1053–1058.
VLDBVLDB-2010-ZhangYJ #approximate #graph #named #scalability
SAPPER: Subgraph Indexing and Approximate Matching in Large Graphs (SZ, JY, WJ), pp. 1185–1194.
STOCSTOC-2010-BhaskaraCCFV #approximate #detection
Detecting high log-densities: an O(n1/4) approximation for densest k-subgraph (AB, MC, EC, UF, AV), pp. 201–210.
STOCSTOC-2010-KollaMST
Subgraph sparsification and nearly optimal ultrasparsifiers (AK, YM, AS, SHT), pp. 57–66.
ICALPICALP-v1-2010-Duan #data type
New Data Structures for Subgraph Connectivity (RD), pp. 201–212.
CIKMCIKM-2010-ZhangLY #graph #named
SUMMA: subgraph matching in massive graphs (SZ, SL, JY), pp. 1285–1288.
ICMLICML-2010-CostaG #distance #kernel #performance
Fast Neighborhood Subgraph Pairwise Distance Kernel (FC, KDG), pp. 255–262.
ICPRICPR-2010-OzdemirA #classification #image #representation #using
Image Classification Using Subgraph Histogram Representation (, SA), pp. 1112–1115.
ICPRICPR-2010-ZhangYWWXHY #graph #multi #recognition
Multi-class Graph Boosting with Subgraph Sharing for Object Recognition (BZ, GY, YW, WW, JX, GH, YY), pp. 1541–1544.
KDDKDD-2010-ZouGL #database #graph #nondeterminism #probability #semantics
Discovering frequent subgraphs over uncertain graph databases under probabilistic semantics (ZZ, HG, JL), pp. 633–642.
STOCSTOC-2009-VassilevskaW
Finding, minimizing, and counting weighted subgraphs (VV, RW), pp. 455–464.
ICALPICALP-v1-2009-AminiFS #morphism
Counting Subgraphs via Homomorphisms (OA, FVF, SS), pp. 71–82.
ICALPICALP-v1-2009-KhullerS #on the
On Finding Dense Subgraphs (SK, BS), pp. 597–608.
ICEISICEIS-J-2009-NguyenH #approach #documentation
Frequent Subgraph-Based Approach for Classifying Vietnamese Text Documents (TANH, KH), pp. 299–308.
CIKMCIKM-2009-KasneciEW #mining #named
MING: mining informative entity relationship subgraphs (GK, SE, GW), pp. 1653–1656.
CIKMCIKM-2009-SunMG #graph #independence #information retrieval #mining
Independent informative subgraph mining for graph information retrieval (BS, PM, CLG), pp. 563–572.
CIKMCIKM-2009-ZouLGZ #graph #mining #nondeterminism
Frequent subgraph pattern mining on uncertain graph data (ZZ, JL, HG, SZ), pp. 583–592.
SIGMODSIGMOD-2008-WangPTT #mining #named #visualisation
CSV: visualizing and mining cohesive subgraphs (NW, SP, KLT, AKHT), pp. 445–458.
VLDBVLDB-2008-ShangZLY #algorithm #morphism #performance #testing #verification
Taming verification hardness: an efficient algorithm for testing subgraph isomorphism (HS, YZ, XL, JXY), pp. 364–375.
VLDBVLDB-2008-WangLLG #documentation #query #xml
Hash-base subgraph query processing method for graph-structured XML documents (HW, JL, JL, HG), pp. 478–489.
STOCSTOC-2008-FakcharoenpholL #algorithm #approximate #problem
An o(log2 k)-approximation algorithm for the k-vertex connected spanning subgraph problem (JF, BL), pp. 153–158.
ICALPICALP-A-2008-ChenTW #complexity #comprehension #morphism
Understanding the Complexity of Induced Subgraph Isomorphisms (YC, MT, MW), pp. 587–596.
GT-VMTGT-VMT-2006-GorpSJ08 #repository
Copying Subgraphs Within Model Repositories (PVG, HS, DJ), pp. 133–145.
DATEDATE-2007-BonziniP #automation #polynomial #set
Polynomial-time subgraph enumeration for automated instruction set extension (PB, LP), pp. 1331–1336.
ICALPICALP-2007-BergerG #graph
Minimum Weight 2-Edge-Connected Spanning Subgraphs in Planar Graphs (AB, MG), pp. 90–101.
AGTIVEAGTIVE-2007-Kortgen #modelling
Modeling Successively Connected Repetitive Subgraphs (ATK), pp. 426–441.
GT-VMTGT-VMT-2007-BalasubramanianNNSTK #graph transformation #model transformation
A Subgraph Operator for Graph Transformation Languages (DB, AN, SN, FS, RT, GK).
CGOCGO-2007-HormatiCM
Exploiting Narrow Accelerators with Data-Centric Subgraph Mapping (AH, NC, SAM), pp. 341–353.
CASECASE-2006-CapachoPGD #assembly #heuristic #problem
Heuristic Methods to Solve the Alternative Subgraphs Assembly Line Balancing Problem (LC, RP, OG, AD), pp. 501–506.
ICALPICALP-v1-2006-VassilevskaWY #graph #problem
Finding the Smallest H-Subgraph in Real Weighted Graphs and Related Problems (VV, RW, RY), pp. 262–273.
KDDKDD-2006-HorvathRW #graph #mining
Frequent subgraph mining in outerplanar graphs (TH, JR, SW), pp. 197–206.
KDDKDD-2006-TongF #performance #problem
Center-piece subgraphs: problem definition and fast solutions (HT, CF), pp. 404–413.
VLDBVLDB-2005-GibsonKT #graph #scalability
Discovering Large Dense Subgraphs in Massive Graphs (DG, RK, AT), pp. 721–732.
STOCSTOC-2004-KortsarzN #algorithm #approximate #graph
Approximation algorithm for k-node connected subgraphs via critical graphs (GK, ZN), pp. 138–145.
ICALPICALP-2004-AlonA #learning
Learning a Hidden Subgraph (NA, VA), pp. 110–121.
KDDKDD-2004-FaloutsosMT #performance
Fast discovery of connection subgraphs (CF, KSM, AT), pp. 118–127.
KDDKDD-2004-HuanWPY #database #graph #mining #named
SPIN: mining maximal frequent subgraphs from graph databases (JH, WW, JP, JY), pp. 581–586.
STOCSTOC-2003-AlonS #graph #testing
Testing subgraphs in directed graphs (NA, AS), pp. 700–709.
CIKMCIKM-2003-SunL #mining #web
Web unit mining: finding and classifying subgraphs of web pages (AS, EPL), pp. 108–115.
STOCSTOC-2002-Chan #geometry
Dynamic subgraph connectivity with geometric applications (TMC), pp. 7–13.
STOCSTOC-2002-CheriyanVV #algorithm #approximate #low cost
Approximation algorithms for minimum-cost k-vertex connected subgraphs (JC, SV, AV), pp. 306–312.
ICPRICPR-v4-2000-FolkersSS #multi #query #using
Processing Pictorial Queries with Multiple Instances Using Isomorphic Subgraphs (AF, HS, AS), pp. 4051–4054.
ICPRICPR-1998-ShearerVB #algorithm #performance #video
An efficient least common subgraph algorithm for video indexing (KS, SV, HB), pp. 1241–1243.
ICALPICALP-1996-Chen #approximate #graph #problem
Practical Approximation Schemes for Maximum Induced-Subgraph Problems on K_{3, 3}-free or K_5-free Graphs (ZZC), pp. 268–279.
DLTDLT-1995-Hartmann #performance
Efficient Subgraph Matching Within Cellular Hypergraphs (PH), pp. 309–318.
STOCSTOC-1994-AlonYZ #graph #named #scalability
Color-coding: a new method for finding simple paths, cycles and other small subgraphs within large graphs (NA, RY, UZ), pp. 326–335.
DACDAC-1993-OhlrichEGS #algorithm #identification #morphism #named #performance #using
SubGemini: Identifying SubCircuits using a Fast Subgraph Isomorphism Algorithm (MO, CE, EG, LS), pp. 31–37.
ICALPICALP-1993-LundY #approximate #problem
The Approximation of Maximum Subgraph Problems (CL, MY), pp. 40–51.
STOCSTOC-1991-DjidjevR #algorithm #performance #problem
An Efficient Algorithm for the Genus Problem with Explicit Construction of Forbidden Subgraphs (HD, JHR), pp. 337–347.
ICALPICALP-1988-LingasS #algorithm #graph #morphism #polynomial
A Polynomial-Time Algorithm for Subgraph Isomorphism of Two-Connected Series-Parallel Graphs (AL, MMS), pp. 394–409.
ICALPICALP-1987-Miyano #algorithm #problem
The Lexicographically First Maximal Subgraph Problems: P-Completeness and NC Algorithms (SM), pp. 425–434.
STOCSTOC-1983-Gabow #network #performance #problem #reduction
An Efficient Reduction Technique for Degree-Constrained Subgraph and Bidirected Network Flow Problems (HNG), pp. 448–456.
STOCSTOC-1978-LapaughR #morphism #problem
The Subgraph Homeomorphism Problem (ASL, RLR), pp. 40–50.
STOCSTOC-1978-Lewis #complexity #on the #problem
On the Complexity of the Maximum Subgraph Problem (JML), pp. 265–274.
STOCSTOC-1976-HuntS #problem #reachability
Dichotomization, Reachability, and the Forbidden Subgraph Problem (Extended Abstract) (HBHI, TGS), pp. 126–134.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
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