Stem big$ (all stems)

219 papers:

DATE-2015-DubenSPYAEPP #big data #case study #energy #performance

Opportunities for energy efficient computing: a study of inexact general purpose processors for high-performance and big-data applications (PDD, JS, P, SY, JA, CCE, KVP, TNP), pp. 764–769.

DATE-2015-KanounS #big data #concept #data type #detection #learning #online #scheduling #streaming

Big-data streaming applications scheduling with online learning and concept drift detection (KK, MvdS), pp. 1547–1550.

DATE-2015-ParkAHYL #big data #energy #gpu #low cost #memory management #performance

Memory fast-forward: a low cost special function unit to enhance energy efficiency in GPU for big data processing (EP, JA, SH, SY, SL), pp. 1341–1346.

DATE-2015-WangLZ #big data #named

SODA: software defined FPGA based accelerators for big data (CW, XL, XZ), pp. 884–887.

HT-2015-Smyth #big data

From Small Sensors to Big Data (BS), p. 101.

PODS-2015-FanGCDL #big data #query

Querying Big Data by Accessing Small Data (WF, FG, YC, TD, PL), pp. 173–184.

PODS-2015-Jordan #big data

Computational Thinking, Inferential Thinking and “Big Data” (MIJ), p. 1.

SIGMOD-2015-CSKZYRPAKDRD #big data #industrial #what #why

Why Big Data Industrial Systems Need Rules and What We Can Do About It (PSGC, CS, KGK, HZ, FY, NR, SP, EA, GK, RD, VR, AD), pp. 265–276.

SIGMOD-2015-DokaPTMK #big data #data analysis #multi #named #workflow

IReS: Intelligent, Multi-Engine Resource Scheduler for Big Data Analytics Workflows (KD, NP, DT, CM, NK), pp. 1451–1456.

SIGMOD-2015-ElgamalYAMH #analysis #big data #component #distributed #named #scalability

sPCA: Scalable Principal Component Analysis for Big Data on Distributed Platforms (TE, MY, AA, WM, MH), pp. 79–91.

SIGMOD-2015-HuangZYDLND0Z #big data #predict

Telco Churn Prediction with Big Data (YH, FZ, MY, KD, YL, BN, WD, QY, JZ), pp. 607–618.

SIGMOD-2015-KhayyatIJMOPQ0Y #big data #named

BigDansing: A System for Big Data Cleansing (ZK, IFI, AJ, SM, MO, PP, JAQR, NT, SY), pp. 1215–1230.

SIGMOD-2015-PerezSBPRSL #graph #interactive #named

Ringo: Interactive Graph Analytics on Big-Memory Machines (YP, RS, AB, RP, MR, PS, JL), pp. 1105–1110.

SIGMOD-2015-RablDFSJ #big data

Just can’t get enough: Synthesizing Big Data (TR, MD, MF, SS, HAJ), pp. 1457–1462.

SIGMOD-2015-SakuraiMF #mining

Mining and Forecasting of Big Time-series Data (YS, YM, CF), pp. 919–922.

SIGMOD-2015-XiaoBME #metadata #summary #using

Even Metadata is Getting Big: Annotation Summarization using InsightNotes (DX, AB, TM, MYE), pp. 1409–1414.

SIGMOD-2015-YuanWYC #big data #database #scalability

A Demonstration of Rubato DB: A Highly Scalable NewSQL Database System for OLTP and Big Data Applications (LYY, LW, JHY, YC), pp. 907–912.

SIGMOD-2015-ZengADAS #analysis #big data #interactive #named #online

G-OLA: Generalized On-Line Aggregation for Interactive Analysis on Big Data (KZ, SA, AD, MA, IS), pp. 913–918.

VLDB-2015-AlyAMAHEO #adaptation #clustering

A Demonstration of AQWA: Adaptive Query-Workload-Aware Partitioning of Big Spatial Data (AMA, ASA, ARM, WGA, MSH, HE, MO), pp. 1968–1979.

VLDB-2015-AlyMHAOEQ #adaptation #clustering #named

AQWA: Adaptive Query-Workload-Aware Partitioning of Big Spatial Data (AMA, ARM, MSH, WGA, MO, HE, TQ), pp. 2062–2073.

VLDB-2015-Balazinska15a #big data #data analysis #industrial #problem #question

Big Data Research: Will Industry Solve all the Problems? (MB), pp. 2053–2064.

VLDB-2015-EldawyMJ #pipes and filters #visualisation

A Demonstration of HadoopViz: An Extensible MapReduce System for Visualizing Big Spatial Data (AE, MFM, CJ), pp. 1896–1907.

VLDB-2015-ElmoreDSBCGHHKK

A Demonstration of the BigDAWG Polystore System (AJE, JD, MS, MB, UÇ, VG, JH, BH, JK, TK, SM, DM, TGM, SP, JP, NT, MV, SZ), pp. 1908–1919.

VLDB-2015-HeGC #corpus #named #semantics #using

SEMA-JOIN: Joining Semantically-Related Tables Using Big Table Corpora (YH, KG, XC), pp. 1358–1369.

VLDB-2015-HuYYDCYGZ #big data #difference #framework #privacy

Differential Privacy in Telco Big Data Platform (XH, MY, JY, YD, LC, QY, HG, JZ), pp. 1692–1703.

VLDB-2015-LoghinTZOT #big data #performance

A Performance Study of Big Data on Small Nodes (DL, BMT, HZ, BCO, YMT), pp. 762–773.

VLDB-2015-SH #approach #big data #named #testing

CODD: A Dataless Approach to Big Data Testing (AS, JRH), pp. 2008–2019.

VLDB-2015-Walter #big data

Big Plateaus of Big Data on the Big Island (TW), pp. 2057–2068.

ICSME-2015-SvajlenkoR #clone detection #detection #tool support

Evaluating clone detection tools with BigCloneBench (JS, CKR), pp. 131–140.

ICALP-v1-2015-Canonne #big data #testing

Big Data on the Rise? — Testing Monotonicity of Distributions (CLC), pp. 294–305.

DUXU-DD-2015-FanHV #big data #risk management

Supply Chain Risk Management in the Era of Big Data (YF, LH, SV), pp. 283–294.

HCI-DE-2015-BoscarioliBSB #challenge #concept #education #how #human-computer #industrial

How to Join Theoretical Concepts, Industry Needs and Innovative Technologies in HCI Courses? The Big Challenge of Teaching HCI (CB, SAB, MSS, SDJB), pp. 27–36.

HIMI-IKD-2015-TrevisanPMG #big data #health #industrial #problem #security #visualisation

Big Data Visualization for Occupational Health and Security Problem in Oil and Gas Industry (DGT, NSP, LM, ACBG), pp. 46–54.

ICEIS-v1-2015-Aghbari #big data #challenge #mining

Mining Big Data — Challenges and Opportunities (ZAA), pp. 379–384.

ICEIS-v1-2015-AnjosFBSGM #big data #search-based

Genetic Mapping of Diseases through Big Data Techniques (JCSdA, BRF, JFB, RBS, CG, UM), pp. 279–286.

ICEIS-v1-2015-EnriquezLGMC #identification #open data #problem

Entity Identification Problem in Big and Open Data (JGE, VL, MG, FJDM, MJEC), pp. 404–408.

ICML-2015-HoangHL #big data #framework #modelling #probability #process

A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data (TNH, QMH, BKHL), pp. 569–578.

KDD-2015-BifetMRHP #big data #classification #data type #evaluation #online #performance

Efficient Online Evaluation of Big Data Stream Classifiers (AB, GDFM, JR, GH, BP), pp. 59–68.

KDD-2015-DhurandharGRME #big data #risk management

Big Data System for Analyzing Risky Procurement Entities (AD, BG, RKR, GM, ME), pp. 1741–1750.

KDD-2015-FeldmanT #approximate #big data #constraints #matrix

More Constraints, Smaller Coresets: Constrained Matrix Approximation of Sparse Big Data (DF, TT), pp. 249–258.

KDD-2015-HsiehLZ #big data #quality #recommendation

Inferring Air Quality for Station Location Recommendation Based on Urban Big Data (HPH, SDL, YZ), pp. 437–446.

KDD-2015-John #big data #case study #how

How Artificial Intelligence and Big Data Created Rocket Fuel: A Case Study (GJ), p. 1629.

KDD-2015-XingHDKWLZXKY #big data #distributed #framework #machine learning #named

Petuum: A New Platform for Distributed Machine Learning on Big Data (EPX, QH, WD, JKK, JW, SL, XZ, PX, AK, YY), pp. 1335–1344.

KDD-2015-YangLJ #big data #data analysis #optimisation

Big Data Analytics: Optimization and Randomization (TY, QL, RJ), p. 2327.

KDD-2015-ZhengYLLSCL #big data #fine-grained #quality

Forecasting Fine-Grained Air Quality Based on Big Data (YZ, XY, ML, RL, ZS, EC, TL), pp. 2267–2276.

POPL-2015-RaychevVK #predict

Predicting Program Properties from “Big Code” (VR, MTV, AK), pp. 111–124.

SAC-2015-KaplanisKSMT

HB+tree: use hadoop and HBase even your data isn’t that big (AK, MK, SS, CM, GT), pp. 973–980.

SAC-2015-Rekha #big data #detection #performance #using

A fast support vector data description system for anomaly detection using big data (AGR), pp. 931–932.

ICSE-v2-2015-NagappanM #big data #re-engineering

Big(ger) Data in Software Engineering (MN, MM), pp. 957–958.

ICSE-v2-2015-ZhouLZLLQ #big data #empirical #framework #quality

An Empirical Study on Quality Issues of Production Big Data Platform (HZ, JGL, HZ, HL, HL, TQ), pp. 17–26.

ASPLOS-2015-Gidra0SSN #big data #garbage collection #named

NumaGiC: a Garbage Collector for Big Data on Big NUMA Machines (LG, GT, JS, MS, NN), pp. 661–673.

ASPLOS-2015-NguyenWBFHX #big data #bound #compilation #named #runtime

FACADE: A Compiler and Runtime for (Almost) Object-Bounded Big Data Applications (KN, KW, YB, LF, JH, G(X), pp. 675–690.

ICST-2015-LiEGO #big data #framework #scalability

A Scalable Big Data Test Framework (NL, AE, YG, JO), pp. 1–2.

ASE-2014-StephenSSE #big data #program analysis

Program analysis for secure big data processing (JJS, SS, RS, PTE), pp. 277–288.

CASE-2014-ChangYLC #behaviour #mining #towards #video

Toward mining anomalous behavior from big moving trajectories in surveillance video (CWC, MHY, CCL, KTC), pp. 1121–1126.

DATE-2014-0002LLCXY #big data #data analysis #energy #network #performance

Energy efficient neural networks for big data analytics (YW, BL, RL, YC, NX, HY), pp. 1–2.

DATE-2014-KimKGH #energy #performance

Utilization-aware load balancing for the energy efficient operation of the big.LITTLE processor (MK, KK, JRG, SH), pp. 1–4.

DocEng-2014-SchmitzP #big data #tool support

Humanist-centric tools for big data: berkeley prosopography services (PS, LP), pp. 179–188.

HT-2014-Hidalgo #big data #comprehension #development #network #social #visualisation

Big data visualization engines for understanding the development of countries, social networks, culture and cities (CAH), p. 3.

PODS-2014-FanGL #big data #independence #on the #query

On scale independence for querying big data (WF, FG, LL), pp. 51–62.

SIGMOD-2014-ChenGLMPVK #manycore #named #scalability

Palette: enabling scalable analytics for big-memory, multicore machines (FC, TG, JL, MM, JP, KV, MK), pp. 705–708.

SIGMOD-2014-FanWW #bound #graph #query

Querying big graphs within bounded resources (WF, XW, YW), pp. 301–312.

SIGMOD-2014-HalperinACCKMORWWXBHS #big data #data transformation

Demonstration of the Myria big data management service (DH, VTdA, LLC, SC, PK, DM, JO, VR, JW, AW, SX, MB, BH, DS), pp. 881–884.

SIGMOD-2014-IstvanWA #big data #data flow

Histograms as a side effect of data movement for big data (ZI, LW, GA), pp. 1567–1578.

SIGMOD-2014-LeFevreSHTPC #big data #data analysis #design #physics

Opportunistic physical design for big data analytics (JL, JS, HH, JT, NP, MJC), pp. 851–862.

SIGMOD-2014-LeFevreSHTPC14a #big data #multi #named #query

MISO: souping up big data query processing with a multistore system (JL, JS, HH, JT, NP, MJC), pp. 1591–1602.

SIGMOD-2014-OzcanTAKMRW #big data #question

Are we experiencing a big data bubble? (FÖ, NT, DJA, MK, CM, KR, JLW), pp. 1407–1408.

SIGMOD-2014-PapailiouTKKK #data transformation #graph #performance #rdf

H2RDF+: an efficient data management system for big RDF graphs (NP, DT, IK, PK, NK), pp. 909–912.

SIGMOD-2014-QinYCCZL #graph #pipes and filters #scalability

Scalable big graph processing in MapReduce (LQ, JXY, LC, HC, CZ, XL), pp. 827–838.

SIGMOD-2014-SolimanAREGSCGRPWNKB #architecture #big data #composition #named #query

Orca: a modular query optimizer architecture for big data (MAS, LA, VR, AEH, ZG, ES, GCC, CGA, FR, MP, FW, SN, KK, RB), pp. 337–348.

SIGMOD-2014-ZoumpatianosIP #big data #interactive

Indexing for interactive exploration of big data series (KZ, SI, TP), pp. 1555–1566.

VLDB-2014-CaoWR #big data #data type #interactive

Interactive Outlier Exploration in Big Data Streams (LC, QW, EAR), pp. 1621–1624.

VLDB-2014-CetintemelDKMMMPSSTTWZ #named #streaming

S-Store: A Streaming NewSQL System for Big Velocity Applications (UÇ, JD, TK, SM, DM, JM, AP, MS, ES, NT, KT, HW, SBZ), pp. 1633–1636.

VLDB-2014-Jiang0OTW #big data #named #scalability

epiC: an Extensible and Scalable System for Processing Big Data (DJ, GC, BCO, KLT, SW), pp. 541–552.

VLDB-2014-KhanE

Systems for Big-Graphs (AK, SE), pp. 1709–1710.

VLDB-2014-LeiZRE #big data #framework #query

Redoop Infrastructure for Recurring Big Data Queries (CL, ZZ, EAR, MYE), pp. 1589–1592.

VLDB-2014-LiLZ #big data #challenge #enterprise

Enterprise Search in the Big Data Era: Recent Developments and Open Challenges (YL, ZL, HZ), pp. 1717–1718.

VLDB-2014-Markl #big data #data analysis #declarative #independence

Breaking the Chains: On Declarative Data Analysis and Data Independence in the Big Data Era (VM), pp. 1730–1733.

VLDB-2014-SimmenSDHLMSTX #big data #graph #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.

VLDB-2014-SuchanekW #big data #data analysis #knowledge base

Knowledge Bases in the Age of Big Data Analytics (FMS, GW), pp. 1713–1714.

VLDB-2014-SuSGOS #big data #java

Changing Engines in Midstream: A Java Stream Computational Model for Big Data Processing (XS, GS, BG, BO, PS), pp. 1343–1354.

VLDB-2014-WuC0SCB #big data #named

yzBigData: Provisioning Customizable Solution for Big Data (SW, GC, KC, LS, HC, HB), pp. 1778–1783.

VLDB-2014-YanCZ #bound

Error-bounded Sampling for Analytics on Big Sparse Data (YY, LJC, ZZ), pp. 1508–1519.

VLDB-2014-YuYWLC #big data #classification #design #detection #power management

Big Data Small Footprint: The Design of A Low-Power Classifier for Detecting Transportation Modes (MCY, TY, SCW, CJL, EYC), pp. 1429–1440.

VLDB-2014-ZhangJSR #big data #recommendation #using

Getting Your Big Data Priorities Straight: A Demonstration of Priority-based QoS using Social-network-driven Stock Recommendation (RZ, RJ, PS, LR), pp. 1665–1668.

VLDB-2015-BuBJCC14 #data flow #graph #named

Pregelix: Big(ger) Graph Analytics on a Dataflow Engine (YB, VRB, JJ, MJC, TC), pp. 161–172.

VLDB-2015-GraefeVKKTLV14 #big data #in memory #performance

In-Memory Performance for Big Data (GG, HV, HK, HAK, JT, ML, ACV), pp. 37–48.

ESOP-2014-PoulsenM #semantics

Deriving Pretty-Big-Step Semantics from Small-Step Semantics (CBP, PDM), pp. 270–289.

ICSME-2014-SvajlenkoIKRM #benchmark #big data #metric #towards

Towards a Big Data Curated Benchmark of Inter-project Code Clones (JS, JFI, IK, CKR, MMM), pp. 476–480.

FLOPS-2014-Riesco #debugging #declarative #maude #semantics #using

Using Big-Step and Small-Step Semantics in Maude to Perform Declarative Debugging (AR), pp. 52–68.

CHI-2014-ReetzG #gesture #identification

Making big gestures: effects of gesture size on observability and identification for co-located group awareness (AR, CG), pp. 4087–4096.

DUXU-DI-2014-Bockermann #approach #big data #data analysis #programming #visual notation

A Visual Programming Approach to Big Data Analytics (CB), pp. 393–404.

EDOC-2014-Ludwig #big data #effectiveness #perspective

Managing Big Data Effectively — A Cloud Provider and a Cloud Consumer Perspective (HL), p. 91.

EDOC-2014-MukkamalaHV #analysis #sentiment #social

Fuzzy-Set Based Sentiment Analysis of Big Social Data (RRM, AH, RKV), pp. 71–80.

CIKM-2014-WangLBLGZ #big data #named

Cleanix: A Big Data Cleaning Parfait (HW, ML, YB, JL, HG, JZ), pp. 2024–2026.

CIKM-2014-YuanWYC #big data #database #grid #scalability #staged

Rubato DB: A Highly Scalable Staged Grid Database System for OLTP and Big Data Applications (LYY, LW, JHY, YC), pp. 1–10.

ECIR-2014-CarageaWCWRCWG #big data #dataset

CiteSeer x : A Scholarly Big Dataset (CC, JW, AMC, KW, JPFR, HHC, ZW, CLG), pp. 311–322.

ICML-c2-2014-Chen0 #big data #learning #modelling #topic #using

Topic Modeling using Topics from Many Domains, Lifelong Learning and Big Data (ZC, BL), pp. 703–711.

ICML-c2-2014-DefazioDC #big data #incremental #named #performance #problem

Finito: A faster, permutable incremental gradient method for big data problems (AD, JD, TSC), pp. 1125–1133.

ICML-c2-2014-TanTWVP #matrix

Riemannian Pursuit for Big Matrix Recovery (MT, IWT, LW, BV, SJP), pp. 1539–1547.

KDD-2014-AhmedDNK #framework #graph

Graph sample and hold: a framework for big-graph analytics (NKA, NGD, JN, RRK), pp. 1446–1455.

KDD-2014-AnagnostopoulosT #big data #scalability

Scaling out big data missing value imputations: pythia vs. godzilla (CA, PT), pp. 651–660.

KDD-2014-Chen0 #big data #documentation #mining #topic

Mining topics in documents: standing on the shoulders of big data (ZC, BL), pp. 1116–1125.

KDD-2014-CormodeD #big data #tutorial

Sampling for big data: a tutorial (GC, NGD), p. 1975.

KDD-2014-Eagle #big data #social

Big data for social good (NE), p. 1522.

KDD-2014-FengGBEHM #big data #database #experience #in memory #query

Management and analytic of biomedical big data with cloud-based in-memory database and dynamic querying: a hands-on experience with real-world data (MF, MG, TB, JE, IH, RM), p. 1970.

KEOD-2014-Bergamaschi #big data #challenge #integration #state of the art

Big Data Integration — State of the Art & Challenges (SB), pp. 1–7.

KEOD-2014-SurynekS #big data #challenge #graph #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.

KEOD-2014-Talia #big data #data mining #distributed #information management #mining

Big Data Mining Services and Distributed Knowledge Discovery Applications on Clouds (DT), pp. 1–5.

KMIS-2014-HeavinDA #big data #information management

Small Data to Big Data — The Information Systems (IS) Continuum (CH, MD, FA), pp. 289–297.

SIGIR-2014-Williams #big data #how

The data revolution: how companies are transforming with big data (HEW), pp. 525–526.

SAC-2014-EvermannA #algorithm #big data #implementation #mining #process

Big data meets process mining: implementing the alpha algorithm with map-reduce (JE, GA), pp. 1414–1416.

FSE-2014-Lam #named #network #social

Omlet: a revolution against big-brother social networks (invited talk) (MSL), p. 1.

HPCA-2014-WangZLZYHGJSZZLZLQ #benchmark #big data #internet #metric #named

BigDataBench: A big data benchmark suite from internet services (LW, JZ, CL, YZ, QY, YH, WG, ZJ, YS, SZ, CZ, GL, KZ, XL, BQ), pp. 488–499.

ICLP-J-2014-TachmazidisAF #big data #performance #semantics

Efficient Computation of the Well-Founded Semantics over Big Data (IT, GA, WF), pp. 445–459.

ECSA-2013-CuestaMF #architecture #realtime #semantics #towards

Towards an Architecture for Managing Big Semantic Data in Real-Time (CEC, MAMP, JDF), pp. 45–53.

HT-2013-LiangCCK #how #modelling #social #social media

How big is the crowd?: event and location based population modeling in social media (YL, JC, ZC, KYK), pp. 99–108.

SIGMOD-2013-AboulnagaB #big data #data analysis

Workload management for big data analytics (AA, SB), pp. 929–932.

SIGMOD-2013-BarnettCDDFGMP #big data #exclamation #interactive

Stat!: an interactive analytics environment for big data (MB, BC, RD, SMD, DF, JG, PM, JCP), pp. 1013–1016.

SIGMOD-2013-CondieMPW #big data #machine learning

Machine learning for big data (TC, PM, NP, MW), pp. 939–942.

SIGMOD-2013-GhazalRHRPCJ #benchmark #big data #data analysis #industrial #metric #named #standard #towards

BigBench: towards an industry standard benchmark for big data analytics (AG, TR, MH, FR, MP, AC, HAJ), pp. 1197–1208.

SIGMOD-2013-LuoT0N

Finding time period-based most frequent path in big trajectory data (WL, HT, LC, LMN), pp. 713–724.

SIGMOD-2013-MishneDLSL #architecture #big data #performance #query #realtime #twitter

Fast data in the era of big data: Twitter’s real-time related query suggestion architecture (GM, JD, ZL, AS, JL), pp. 1147–1158.

SIGMOD-2013-NazarukR #big data

Big data in capital markets (AN, MR), pp. 917–918.

SIGMOD-2013-SuchanekW #big data

Knowledge harvesting in the big-data era (FMS, GW), pp. 933–938.

SIGMOD-2013-SumbalyKS #big data #ecosystem

The big data ecosystem at LinkedIn (RS, JK, SS), pp. 1125–1134.

VLDB-2013-BediniEV #big data #case study #framework #scalability

The Trento Big Data Platform for Public Administration and Large Companies: Use cases and Opportunities (IB, BE, YV), pp. 1166–1167.

VLDB-2013-BellamkondaLJZLC #adaptation #big data #execution #parallel

Adaptive and Big Data Scale Parallel Execution in Oracle (SB, HGL, UJ, YZ, VL, TC), pp. 1102–1113.

VLDB-2013-ChandramouliGQ #big data #in the cloud #scalability

Scalable Progressive Analytics on Big Data in the Cloud (BC, JG, AQ), pp. 1726–1737.

VLDB-2013-ChirkovaY #question #what

Big and Useful: What’s in the Data for Me? (RC, JY), pp. 1390–1391.

VLDB-2013-DongS #big data #integration

Big Data Integration (XLD, DS), pp. 1188–1189.

VLDB-2013-FanGN #big data #preprocessor #query

Making Queries Tractable on Big Data with Preprocessing (WF, FG, FN), pp. 685–696.

VLDB-2013-Franceschini #approach #big data #how #open source

How to maximize the value of big data with the open source SpagoBI suite through a comprehensive approach (MF), pp. 1170–1171.

VLDB-2013-Hoppe #automation #big data #learning #ontology #web

Automatic ontology-based User Profile Learning from heterogeneous Web Resources in a Big Data Context (AH), pp. 1428–1433.

VLDB-2013-LeeL #clustering #graph #query #rdf #scalability #semantics

Scaling Queries over Big RDF Graphs with Semantic Hash Partitioning (KL, LL), pp. 1894–1905.

VLDB-2013-RamazzinaBS #framework

A New Service for Customer Care Based on the TrentoRise BigData Platform (SR, CLB, DS), pp. 1162–1163.

VLDB-2013-SathiamoorthyAPDVCB #big data #novel

XORing Elephants: Novel Erasure Codes for Big Data (MS, MA, DSP, AGD, RV, SC, DB), pp. 325–336.

VLDB-2013-TranBD #big data #design #problem #query

Designing Query Optimizers for Big Data Problems of The Future (NT, SB, JD), pp. 1168–1169.

ESOP-2013-Chargueraud #semantics

Pretty-Big-Step Semantics (AC), pp. 41–60.

ICALP-v2-2013-BachrachP #big data #performance #pseudo #recommendation #sketching #using

Sketching for Big Data Recommender Systems Using Fast Pseudo-random Fingerprints (YB, EP), pp. 459–471.

IFM-2013-Ciobaca #automation #semantics

From Small-Step Semantics to Big-Step Semantics, Automatically (SC), pp. 347–361.

GCM-J-2012-FaithfullPH #development #graph

Big Red: A Development Environment for Bigraphs (AJF, GP, TTH).

DUXU-WM-2013-LiuVMM #big data #design #experience #framework #interactive #mining #visualisation

Designing Discovery Experience for Big Data Interaction: A Case of Web-Based Knowledge Mining and Interactive Visualization Platform (QL, MV, KPCM, AFM), pp. 543–552.

HIMI-LCCB-2013-FlachsbartEH #human-computer #mobile #question

Are HCI Issues a Big Factor in Supply Chain Mobile Apps? (BF, CCE, MGH), pp. 450–456.

CIKM-2013-Giles #big data #data mining #information management #mining

Scholarly big data: information extraction and data mining (CLG), pp. 1–2.

CIKM-2013-LuoFHWB #bisimulation #graph #memory management #reduction

External memory K-bisimulation reduction of big graphs (YL, GHLF, JH, YW, PDB), pp. 919–928.

KDD-2013-CannyZ #big data #data analysis

Big data analytics with small footprint: squaring the cloud (JC, HZ), pp. 95–103.

KDD-2013-GetoorM #big data

Entity resolution for big data (LG, AM), p. 1527.

KDD-2013-Neumann #big data #problem #using

Using “big data” to solve “small data” problems (CN), p. 1140.

KDD-2013-RamanSGJ #big data #pipes and filters

Beyond myopic inference in big data pipelines (KR, AS, JG, TJ), pp. 86–94.

KDD-2013-SunR #big data #data analysis

Big data analytics for healthcare (JS, CKR), p. 1525.

KDD-2013-ZhengLH #big data #named #quality

U-Air: when urban air quality inference meets big data (YZ, FL, HPH), pp. 1436–1444.

MLDM-2013-Suthaharan #big data #classification #network

A Single-Domain, Representation-Learning Model for Big Data Classification of Network Intrusion (SS), pp. 296–310.

SEKE-2013-Khoshgoftaar #big data #challenge

Overcoming Big Data Challenges (TMK).

SIGIR-2013-Smith #big data #multi

Riding the multimedia big data wave (JRS), pp. 1–2.

MoDELS-2013-FondementMTWF #metamodelling

Big Metamodels Are Evil — Package Unmerge — A Technique for Downsizing Metamodels (FF, PAM, LT, BW, GF), pp. 138–153.

MoDELS-2013-FondementMTWF #metamodelling

Big Metamodels Are Evil — Package Unmerge — A Technique for Downsizing Metamodels (FF, PAM, LT, BW, GF), pp. 138–153.

ICSE-2013-ShangJHAHM #big data #data analysis #developer

Assisting developers of big data analytics applications when deploying on hadoop clouds (WS, ZMJ, HH, BA, AEH, PM), pp. 402–411.

HPCA-2013-ZhuR #energy #mobile #web

High-performance and energy-efficient mobile web browsing on big/little systems (YZ, VJR), pp. 13–24.

HPDC-2013-XuS0 #big data #named

IBIS: interposed big-data I/O scheduler (YX, AS, MZ), pp. 109–110.

ISMM-2013-BuBXC #big data #design

A bloat-aware design for big data applications (YB, VRB, G(X, MJC), pp. 119–130.

PPoPP-2013-ParkST #parallel #programming

Parallel programming with big operators (CP, GLSJ, JBT), pp. 293–294.

ICLP-J-2013-CostaV #named

BigYAP: Exo-compilation meets UDI (VSC, DV), pp. 799–813.

WICSA-ECSA-2012-BegoliH #big data #design #effectiveness #information management

Design Principles for Effective Knowledge Discovery from Big Data (EB, JLH), pp. 215–218.

DAC-2012-Jeff #architecture #migration #multi

Big.LITTLE system architecture from ARM: saving power through heterogeneous multiprocessing and task context migration (BJ), pp. 1143–1146.

DocEng-2012-JanssenSBWS #documentation #named

Receipts2Go: the big world of small documents (BJ, ES, EAB, PW, MAS), pp. 121–124.

PODS-2012-Chaudhuri #big data #data transformation #research #what

What next?: a half-dozen data management research goals for big data and the cloud (SC), pp. 1–4.

SIGMOD-2012-ChengQR #big data #data analysis #named

GLADE: big data analytics made easy (YC, CQ, FR), pp. 697–700.

VLDB-2012-AlsubaieeAABBBCGHKLOPVW #analysis #big data #data transformation #named #open source

ASTERIX: An Open Source System for “Big Data” Management and Analysis (SA, YA, HA, AB, VRB, YB, MJC, RG, ZH, YSK, CL, NO, PP, RV, JW), pp. 1898–1901.

VLDB-2012-ChenAK #big data #interactive #pipes and filters

Interactive Analytical Processing in Big Data Systems: A Cross-Industry Study of MapReduce Workloads (YC, SA, RHK), pp. 1802–1813.

VLDB-2012-DittrichQ #big data #performance #pipes and filters

Efficient Big Data Processing in Hadoop MapReduce (JD, JAQR), pp. 2014–2015.

VLDB-2012-LabrinidisJ #big data #challenge

Challenges and Opportunities with Big Data (AL, HVJ), pp. 2032–2033.

VLDB-2012-RablSJGMM #big data #challenge #enterprise #performance

Solving Big Data Challenges for Enterprise Application Performance Management (TR, MS, HAJ, SGV, VMM, SM), pp. 1724–1735.

VLDB-2012-Shim #algorithm #big data #data analysis #pipes and filters

MapReduce Algorithms for Big Data Analysis (KS), pp. 2016–2017.

VLDB-2012-XuLGC #analysis #big data #clustering #in the cloud #interactive #named #visual notation

CloudVista: Interactive and Economical Visual Cluster Analysis for Big Data in the Cloud (HX, ZL, SG, KC), pp. 1886–1889.

VLDB-2012-ZhangY #array #optimisation

Optimizing I/O for Big Array Analytics (YZ, JY), pp. 764–775.

CIKM-2012-TanLN #data analysis #named

CloST: a hadoop-based storage system for big spatio-temporal data analytics (HT, WL, LMN), pp. 2139–2143.

ICML-2012-KleinerTSJ #big data

The Big Data Bootstrap (AK, AT, PS, MIJ), p. 232.

KDD-2012-Jordan #big data #divide and conquer #statistics

Divide-and-conquer and statistical inference for big data (MIJ), p. 4.

KDD-2012-Kitsuregawa #big data

Building an engine for big data (MK), p. 223.

SIGIR-2012-Baeza-YatesM #web

(Big) usage data in web search (RABY, YM), pp. 1181–1182.

ECOOP-2012-Ancona #induction #object-oriented #semantics

Soundness of Object-Oriented Languages with Coinductive Big-Step Semantics (DA), pp. 459–483.

RE-2012-Cleland-HuangMMA #recommendation #traceability

Breaking the big-bang practice of traceability: Pushing timely trace recommendations to project stakeholders (JCH, PM, MM, SA), pp. 231–240.

ICSE-2012-Faghih #modelling

Model translations among big-step modeling languages (FF), pp. 1555–1558.

HPDC-2012-Budiu #artificial reality #big data #framework

Putting a “big-data” platform to good use: training kinect (MB), pp. 1–2.

VLDB-2011-Campbell #big data #question

Is It Still “Big Data” If It Fits In My Pocket? (DC), p. 694.

FASE-2011-EsmaeilsabzaliD #modelling #quality #semantics

Semantic Quality Attributes for Big-Step Modelling Languages (SE, NAD), pp. 65–80.

CEFP-2011-Pali

Extending Little Languages into Big Systems (GP), pp. 499–516.

HIMI-v2-2011-TakahashiT #information management

Big Fat Wand: A Laser Projection System for Information Sharing in a Workspace (TT, TT), pp. 403–410.

GPCE-2011-EsmaeilsabzaliFA #aspect-oriented #automation #modelling #monitoring

Monitoring aspects for the customization of automatically generated code for big-step models (SE, BF, JMA), pp. 117–126.

SIGMOD-2010-Amer-YahiaDKKF #algorithm #big data

Crowds, clouds, and algorithms: exploring the human side of “big data” applications (SAY, AD, JMK, NK, MJF), pp. 1259–1260.

VLDB-2010-AgrawalDA #big data #in the cloud #question

Big Data and Cloud Computing: New Wine or just New Bottles? (DA, SD, AEA), pp. 1647–1648.

ESOP-2010-NakataU #hoare #induction #logic #semantics

A Hoare Logic for the Coinductive Trace-Based Big-Step Semantics of While (KN, TU), pp. 488–506.

FASE-2010-EsmaeilsabzaliD #modelling #semantics

Prescriptive Semantics for Big-Step Modelling Languages (SE, NAD), pp. 158–172.

RE-2010-MavinW #approach #requirements

Big Ears (The Return of “Easy Approach to Requirements Engineering”) (AM, PW), pp. 277–282.

FSE-2010-Eagle #big data #development #social

Big data, global development, and complex social systems (NE), pp. 3–4.

SAT-2010-Naveh #constraints #difference

The Big Deal: Applying Constraint Satisfaction Technologies Where It Makes the Difference (YN), pp. 1–7.

VLDB-2009-CohenDDHW #analysis #big data

MAD Skills: New Analysis Practices for Big Data (JC, BD, MD, JMH, CW), pp. 1481–1492.

HCI-AUII-2009-FarajMV #mobile #named

BigKey: A Virtual Keyboard for Mobile Devices (KAF, MM, NV), pp. 3–10.

HCI-NT-2009-BellottiFAS #design #evaluation

User-Centered Design and Evaluation — The Big Picture (VB, SF, TA, SS), pp. 214–223.

RE-2009-EsmaeilsabzaliDAN #modelling #semantics

Semantic Criteria for Choosing a Language for Big-Step Models (SE, NAD, JMA, JN), pp. 181–190.

ASPLOS-2009-AleenC #analysis #commutative #parallel #program transformation

Commutativity analysis for software parallelization: letting program transformations see the big picture (FA, NC), pp. 241–252.

VLDB-2008-DittrichBS #how #question

Dwarfs in the rearview mirror: how big are they really? (JD, LB, MAVS), pp. 1586–1597.

SAC-2008-GronauR #implementation #information management

Information systems implementation: the big picture (NG, MR), pp. 1077–1078.

SAC-2008-MattosLFM #clustering #documentation #framework #named

BigBatch: a document processing platform for clusters and grids (GdOM, RDL, AdAF, FMJM), pp. 434–441.

SPLC-2008-Krueger #framework #product line

The BigLever Software Gears Unified Software Product Line Engineering Framework (CWK), p. 353.

CGO-2007-Fang #parallel #programming

Parallel Programming Environment: A Key to Translating Tera-Scale Platforms into a Big Success (JF), p. 18.

PPoPP-2007-Fang #parallel #programming

Parallel programming environment: a key to translating tera-scale platforms into a big success (JZF), p. 1.

DATE-2006-MarculescuRS #design #idea #network #question

Is “Network” the next “Big Idea” in design? (RM, JMR, ALSV), pp. 254–256.

ESOP-2006-Leroy #induction #semantics

Coinductive Big-Step Operational Semantics (XL), pp. 54–68.

DocEng-2005-LinsA #documentation #named

BigBatch: a toolbox for monochromatic documents (RDL, BTÁ), pp. 239–240.

CSEET-2005-BleekLS #education #experience #industrial #re-engineering

Transferring Experience from Software Engineering Training in Industry to Mass University Education — The Big Picture (WGB, CL, AS), pp. 195–203.

ECOOP-2005-GibbsLC #aspect-oriented #evolution #framework #question

Sustainable System Infrastructure and Big Bang Evolution: Can Aspects Keep Pace? (CG, CRL, YC), pp. 241–261.

FoSSaCS-1998-Heckmann #integer #linear

The Appearance of Big Integers in Exact Real Arithmetic Based on Linear Fractional Transformations (RH), pp. 172–188.

ICALP-1997-ErdosSSW #sequence

Constructing Big Trees from Short Sequences (PLE, MAS, LAS, TW), pp. 827–837.

ICFP-1997-McAdam #ml

BigTypes in ML (BJM), p. 316.

PODS-1995-Papadimitriou #database #query

Database Metatheory: Asking the Big Queries (CHP), pp. 1–10.

VLDB-1995-BrownS #named

BigSur: A System For the Management of Earth Science Data (PB, MS), pp. 720–728.

SIGIR-1995-Riloff #classification #difference #word

Little Words Can Make a Big Difference for Text Classification (ER), pp. 130–136.