BibSLEIGH — Proceedings of the 15th International Conference on Knowledge Discovery and Data Mining

John F. Elder IV, Françoise Fogelman-Soulié, Peter A. Flach, Mohammed Javeed Zaki
Proceedings of the 15th International Conference on Knowledge Discovery and Data Mining
KDD, 2009.

KER

@proceedings{KDD-2009,
	address       = "Paris, France",
	editor        = "John F. Elder IV and Françoise Fogelman-Soulié and Peter A. Flach and Mohammed Javeed Zaki",
	isbn          = "978-1-60558-495-9",
	publisher     = "{ACM}",
	title         = "{Proceedings of the 15th International Conference on Knowledge Discovery and Data Mining}",
	year          = 2009,
}

Contents (144 items)

KDD-2009-Hand #data mining #mining #modelling #tool support: Mismatched models, wrong results, and dreadful decisions: on choosing appropriate data mining tools (DJH), pp. 1–2.
KDD-2009-Kumar #challenge #mining #web: Mining web logs: applications and challenges (RK), pp. 3–4.
KDD-2009-Mannila #data mining #mining: Randomization methods in data mining (HM), pp. 5–6.
KDD-2009-Srivastava #data mining #mining: Data mining at NASA: from theory to applications (ANS), pp. 7–8.
KDD-2009-Wasserman #network #statistics: Network science: an introduction to recent statistical approaches (SW), pp. 9–10.
KDD-2009-AgarwalC #modelling: Regression-based latent factor models (DA, BCC), pp. 19–28.
KDD-2009-AggarwalLWW #mining #nondeterminism: Frequent pattern mining with uncertain data (CCA, YL, JW, JW), pp. 29–38.
KDD-2009-AhmedXCM #biology #mining #modelling #topic: Structured correspondence topic models for mining captioned figures in biological literature (AA, EPX, WWC, RFM), pp. 39–48.
KDD-2009-AmbekarWMMS #classification #open source: Name-ethnicity classification from open sources (AA, CBW, JM, SM, SS), pp. 49–58.
KDD-2009-AndoS #clustering #detection: Detection of unique temporal segments by information theoretic meta-clustering (SA, ES), pp. 59–68.
KDD-2009-AshrafiN: Collusion-resistant anonymous data collection method (MZA, SKN), pp. 69–78.
KDD-2009-AsurP #analysis #approach #graph #interactive: A viewpoint-based approach for interaction graph analysis (SA, SP), pp. 79–88.
KDD-2009-BackstromKK #optimisation #problem #scheduling #web: Optimizing web traffic via the media scheduling problem (LB, JMK, RK), pp. 89–98.
KDD-2009-BekkermanSV #clustering #combinator: Improving clustering stability with combinatorial MRFs (RB, MS, KV), pp. 99–108.
KDD-2009-BerlingerioPNG #data analysis #interactive #mining #workflow: Temporal mining for interactive workflow data analysis (MB, FP, MN, FG), pp. 109–118.
KDD-2009-BerneckerKRVZ #database #mining #nondeterminism #probability: Probabilistic frequent itemset mining in uncertain databases (TB, HPK, MR, FV, AZ), pp. 119–128.
KDD-2009-BeygelzimerL #learning: The offset tree for learning with partial labels (AB, JL), pp. 129–138.
KDD-2009-BifetHPKG #data type #evolution: New ensemble methods for evolving data streams (AB, GH, BP, RK, RG), pp. 139–148.
KDD-2009-BohmHMP #detection #named: CoCo: coding cost for parameter-free outlier detection (CB, KH, NSM, CP), pp. 149–158.
KDD-2009-BuCFL #monitoring #performance: Efficient anomaly monitoring over moving object trajectory streams (YB, LC, AWCF, DL), pp. 159–168.
KDD-2009-ChangBB #network #social: Connections between the lines: augmenting social networks with text (JC, JLBG, DMB), pp. 169–178.
KDD-2009-ChenLTW #adaptation #concept #mining: Extracting discriminative concepts for domain adaptation in text mining (BC, WL, IWT, TLW), pp. 179–188.
KDD-2009-ChenCBT #learning #optimisation #random: Constrained optimization for validation-guided conditional random field learning (MC, YC, MRB, AET), pp. 189–198.
KDD-2009-ChenWY #network #performance #social: Efficient influence maximization in social networks (WC, YW, SY), pp. 199–208.
KDD-2009-ChenPC #behaviour #scalability: Large-scale behavioral targeting (YC, DP, JFC), pp. 209–218.
KDD-2009-ChierichettiKLMPR #network #on the #social: On compressing social networks (FC, RK, SL, MM, AP, PR), pp. 219–228.
KDD-2009-Delage #library #online #ranking: Regret-based online ranking for a growing digital library (ED), pp. 229–238.
KDD-2009-DengLK #algorithm #graph: A generalized Co-HITS algorithm and its application to bipartite graphs (HD, MRL, IK), pp. 239–248.
KDD-2009-DeodharG #mining #predict: Mining for the most certain predictions from dyadic data (MD, JG), pp. 249–258.
KDD-2009-DonmezCS #learning: Efficiently learning the accuracy of labeling sources for selective sampling (PD, JGC, JGS), pp. 259–268.
KDD-2009-DuFWA #communication #generative #network #scalability: Large human communication networks: patterns and a utility-driven generator (ND, CF, BW, LA), pp. 269–278.
KDD-2009-DundarHBRR #case study #dataset #detection #learning #using: Learning with a non-exhaustive training dataset: a case study: detection of bacteria cultures using optical-scattering technology (MD, EDH, AKB, JPR, BR), pp. 279–288.
KDD-2009-El-AriniVSG: Turning down the noise in the blogosphere (KEA, GV, DS, CG), pp. 289–298.
KDD-2009-FormanSR #classification #linear: Feature shaping for linear SVM classifiers (GF, MS, SR), pp. 299–308.
KDD-2009-FrankEK #approach #classification #multi: A multi-relational approach to spatial classification (RF, ME, AJK), pp. 309–318.
KDD-2009-FrenoTG #estimation #hybrid #pseudo #random #scalability: Scalable pseudo-likelihood estimation in hybrid random fields (AF, ET, MG), pp. 319–328.
KDD-2009-GamaSR #algorithm #evaluation #learning: Issues in evaluation of stream learning algorithms (JG, RS, PPR), pp. 329–338.
KDD-2009-GaoFSH #learning: Heterogeneous source consensus learning via decision propagation and negotiation (JG, WF, YS, JH), pp. 339–348.
KDD-2009-GeXZSGW #learning #multi: Multi-focal learning and its application to customer service support (YG, HX, WZ, RKS, XG, WW), pp. 349–358.
KDD-2009-GuZ #clustering: Co-clustering on manifolds (QG, JZ), pp. 359–368.
KDD-2009-GuoTCZZ #generative #network #online #social: Analyzing patterns of user content generation in online social networks (LG, ET, SC, XZ, YEZ), pp. 369–378.
KDD-2009-HanhijarviOVPTM #data mining #mining: Tell me something I don’t know: randomization strategies for iterative data mining (SH, MO, NV, KP, NT, HM), pp. 379–388.
KDD-2009-HuZLPZ #clustering #documentation #wiki: Exploiting Wikipedia as external knowledge for document clustering (XH, XZ, CL, EKP, XZ), pp. 389–396.
KDD-2009-JamaliE #named #random #recommendation #trust: TrustWalker: a random walk model for combining trust-based and item-based recommendation (MJ, ME), pp. 397–406.
KDD-2009-JiYLZKY #interactive #using: Drosophila gene expression pattern annotation using sparse features and term-term interactions (SJ, LY, YXL, ZHZ, SK, JY), pp. 407–416.
KDD-2009-JinXL #representation #set: Cartesian contour: a concise representation for a collection of frequent sets (RJ, YX, LL), pp. 417–426.
KDD-2009-KolczC #composition #email: Genre-based decomposition of email class noise (AK, GVC), pp. 427–436.
KDD-2009-KoopmanS #relational: Characteristic relational patterns (AK, AS), pp. 437–446.
KDD-2009-Koren #collaboration: Collaborative filtering with temporal dynamics (YK), pp. 447–456.
KDD-2009-KulkarniSRC #web #wiki: Collective annotation of Wikipedia entities in web text (SK, AS, GR, SC), pp. 457–466.
KDD-2009-LappasLT #network #social: Finding a team of experts in social networks (TL, KL, ET), pp. 467–476.
KDD-2009-LappasAPKG #documentation #on the #sequence: On burstiness-aware search for document sequences (TL, BA, MP, DK, DG), pp. 477–486.
KDD-2009-Last #data mining #mining: Improving data mining utility with projective sampling (ML), pp. 487–496.
KDD-2009-LeskovecBK: Meme-tracking and the dynamics of the news cycle (JL, LB, JMK), pp. 497–506.
KDD-2009-LiMPF #mining #named #sequence #summary: DynaMMo: mining and summarization of coevolving sequences with missing values (LL, JM, NSP, CF), pp. 507–516.
KDD-2009-LiL #on the #privacy #trade-off: On the tradeoff between privacy and utility in data publishing (TL, NL), pp. 517–526.
KDD-2009-LinSCKSK #community #named #relational: MetaFac: community discovery via relational hypergraph factorization (YRL, JS, PC, RBK, HS, AK), pp. 527–536.
KDD-2009-LiuGF #named: BBM: bayesian browsing model from petabyte-scale data (CL, FG, CF), pp. 537–546.
KDD-2009-LiuCY #scalability: Large-scale sparse logistic regression (JL, JC, JY), pp. 547–556.
KDD-2009-LoCHKS #approach #behaviour #classification #detection #mining: Classification of software behaviors for failure detection: a discriminative pattern mining approach (DL, HC, JH, SCK, CS), pp. 557–566.
KDD-2009-LoscalzoYD #feature model: Consensus group stable feature selection (SL, LY, CHQD), pp. 567–576.
KDD-2009-LozanoALR #modelling #visual notation: Grouped graphical Granger modeling methods for temporal causal modeling (ACL, NA, YL, SR), pp. 577–586.
KDD-2009-LozanoLNLPHA #modelling: Spatial-temporal causal modeling for climate change attribution (ACL, HL, ANM, YL, CP, JRMH, NA), pp. 587–596.
KDD-2009-Macskassy #empirical #graph #learning #metric #using: Using graph-based metrics with empirical risk minimization to speed up active learning on networked data (SAM), pp. 597–606.
KDD-2009-MalmgrenHAW #communication: Characterizing individual communication patterns (RDM, JMH, LANA, DJW), pp. 607–616.
KDD-2009-MaunzHK #graph #mining #refinement #scalability #using: Large-scale graph mining using backbone refinement classes (AM, CH, SK), pp. 617–626.
KDD-2009-McSherryM #privacy #recommendation: Differentially Private Recommender Systems: Building Privacy into the Netflix Prize Contenders (FM, IM), pp. 627–636.
KDD-2009-MonrealePTG #mining #named #predict: WhereNext: a location predictor on trajectory pattern mining (AM, FP, RT, FG), pp. 637–646.
KDD-2009-NijssenGR #approach #constraints #correlation #mining #programming: Correlated itemset mining in ROC space: a constraint programming approach (SN, TG, LDR), pp. 647–656.
KDD-2009-OnumaTF #algorithm #named #novel #recommendation: TANGENT: a novel, “Surprise me”, recommendation algorithm (KO, HT, CF), pp. 657–666.
KDD-2009-PanS #collaboration #scalability: Mind the gaps: weighting the unknown in large-scale one-class collaborative filtering (RP, MS), pp. 667–676.
KDD-2009-PandeyASMK #analysis #approach #clustering: An association analysis approach to biclustering (GP, GA, MS, CLM, VK), pp. 677–686.
KDD-2009-PoernomoG #named #representation: CP-summary: a concise representation for browsing frequent itemsets (AKP, VG), pp. 687–696.
KDD-2009-PoernomoG09a #fault tolerance #mining #performance #towards: Towards efficient mining of proportional fault-tolerant frequent itemsets (AKP, VG), pp. 697–706.
KDD-2009-ProvostDHZM #network #online #privacy #social: Audience selection for on-line brand advertising: privacy-friendly social network targeting (FJP, BD, RH, XZ, AM), pp. 707–716.
KDD-2009-QiD #clustering #flexibility #framework: A principled and flexible framework for finding alternative clusterings (ZQ, ID), pp. 717–726.
KDD-2009-RendleMNS #learning #ranking #recommendation: Learning optimal ranking with tensor factorization for tag recommendation (SR, LBM, AN, LST), pp. 727–736.
KDD-2009-SatuluriP #clustering #community #graph #probability #scalability #using: Scalable graph clustering using stochastic flows: applications to community discovery (VS, SP), pp. 737–746.
KDD-2009-ScrippsTE #analysis #network #preprocessor: Measuring the effects of preprocessing decisions and network forces in dynamic network analysis (JS, PNT, AHE), pp. 747–756.
KDD-2009-ShenJY #matrix #mining: Mining discrete patterns via binary matrix factorization (BHS, SJ, JY), pp. 757–766.
KDD-2009-ShiJ #linear #statistics: Anomalous window discovery through scan statistics for linear intersecting paths (SSLIP) (LS, VPJ), pp. 767–776.
KDD-2009-ShiZCZ #behaviour #online: User grouping behavior in online forums (XS, JZ, RC, LZ), pp. 777–786.
KDD-2009-ShibuyaHK #modelling #multi #quantifier: Causality quantification and its applications: structuring and modeling of multivariate time series (TS, TH, YK), pp. 787–796.
KDD-2009-SunYH #clustering #network: Ranking-based clustering of heterogeneous information networks with star network schema (YS, YY, JH), pp. 797–806.
KDD-2009-TangSWY #analysis #network #scalability #social: Social influence analysis in large-scale networks (JT, JS, CW, ZY), pp. 807–816.
KDD-2009-TangL #learning #relational #social: Relational learning via latent social dimensions (LT, HL), pp. 817–826.
KDD-2009-TantipathananandhB #algorithm #approximate #community #identification: Constant-factor approximation algorithms for identifying dynamic communities (CT, TYBW), pp. 827–836.
KDD-2009-TsourakakisKMF #graph #named: DOULION: counting triangles in massive graphs with a coin (CET, UK, GLM, CF), pp. 837–846.
KDD-2009-VatturiW #detection #using: Category detection using hierarchical mean shift (PV, WKW), pp. 847–856.
KDD-2009-WangSAL #fault #learning #network: Learning, indexing, and diagnosing network faults (TW, MS, DA, LL), pp. 857–866.
KDD-2009-WangCP #aspect-oriented #mining #query: Mining broad latent query aspects from search sessions (XW, DC, KP), pp. 867–876.
KDD-2009-WuXC #adaptation #clustering #metric: Adapting the right measures for K-means clustering (JW, HX, JC), pp. 877–886.
KDD-2009-WuSJRG #detection #framework #performance: A LRT framework for fast spatial anomaly detection (MW, XS, CJ, SR, JG), pp. 887–896.
KDD-2009-XueW #classification #quantifier: Quantification and semi-supervised classification methods for handling changes in class distribution (JCX, GMW), pp. 897–906.
KDD-2009-YanHJ #approximate #clustering #performance: Fast approximate spectral clustering (DY, LH, MIJ), pp. 907–916.
KDD-2009-YangSWC #classification #effectiveness #learning #multi: Effective multi-label active learning for text classification (BY, JTS, TW, ZC), pp. 917–926.
KDD-2009-YangJCZ #approach #community #detection: Combining link and content for community detection: a discriminative approach (TY, RJ, YC, SZ), pp. 927–936.
KDD-2009-YaoMM #documentation #model inference #performance #streaming #topic: Efficient methods for topic model inference on streaming document collections (LY, DMM, AM), pp. 937–946.
KDD-2009-YeK #data mining #mining: Time series shapelets: a new primitive for data mining (LY, EJK), pp. 947–956.
KDD-2009-YinLMH #classification #graph #social #web: Exploring social tagging graph for web object classification (ZY, RL, QM, JH), pp. 957–966.
KDD-2009-YooYLM #email #mining #network #personalisation #social: Mining social networks for personalized email prioritization (SY, YY, FL, ICM), pp. 967–976.
KDD-2009-YouHC #biology #learning #network: Learning patterns in the dynamics of biological networks (CHY, LBH, DJC), pp. 977–986.
KDD-2009-ZhangFPGS #streaming #towards: Toward autonomic grids: analyzing the job flow with affinity streaming (XZ, CF, JP, CGR, MS), pp. 987–996.
KDD-2009-ZhangWWZ #community #detection #network #parallel #scalability: Parallel community detection on large networks with propinquity dynamics (YZ, JW, YW, LZ), pp. 997–1006.
KDD-2009-ZhelevaSG #co-evolution #network #social: Co-evolution of social and affiliation networks (EZ, HS, LG), pp. 1007–1016.
KDD-2009-ZhengWLL: Information theoretic regularization for semi-supervised boosting (LZ, SW, YL, CHL), pp. 1017–1026.
KDD-2009-ZhongFPZRTV #adaptation #kernel: Cross domain distribution adaptation via kernel mapping (EZ, WF, JP, KZ, JR, DST, OV), pp. 1027–1036.
KDD-2009-ZhuM #mining #web: Mining rich session context to improve web search (GZ, GM), pp. 1037–1046.
KDD-2009-ZhuXZ #markov #network: Primal sparse Max-margin Markov networks (JZ, EPX, BZ), pp. 1047–1056.
KDD-2009-ZhuWKL #mining: Augmenting the generalized hough transform to enable the mining of petroglyphs (QZ, XW, EJK, SHL), pp. 1057–1066.
KDD-2009-AttenbergPS #behaviour #modelling #predict: Modeling and predicting user behavior in sponsored search (JA, SP, TS), pp. 1067–1076.
KDD-2009-BhattacharyaGGVAE: Enabling analysts in managed services for CRM analytics (IB, SG, AG, AV, JA, KE), pp. 1077–1086.
KDD-2009-CherkasovaEMTV #algorithm #enterprise #information management #similarity: Applying syntactic similarity algorithms for enterprise information management (LC, KE, CBMI, JT, ACV), pp. 1087–1096.
KDD-2009-ChuPBMPCZ #analysis #behaviour #case study #exclamation: A case study of behavior-driven conjoint analysis on Yahoo!: front page today module (WC, STP, TB, NM, AP, SC, JZ), pp. 1097–1104.
KDD-2009-CrookFKL #web: Seven pitfalls to avoid when running controlled experiments on the web (TC, BF, RK, RL), pp. 1105–1114.
KDD-2009-DaruruMWG #clustering #data flow #data mining #mining #parallel #pervasive #scalability: Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data (SD, NMM, MW, JG), pp. 1115–1124.
KDD-2009-DingLZ #mining: Entity discovery and assignment for opinion mining applications (XD, BL, LZ), pp. 1125–1134.
KDD-2009-DuJDLT #approach #migration #mining: Migration motif: a spatial — temporal pattern mining approach for financial markets (XD, RJ, LD, VEL, JHTJ), pp. 1135–1144.
KDD-2009-FuxmanKGATS #automation #classification #using: Improving classification accuracy using automatically extracted training data (AF, AK, ABG, RA, PT, JCS), pp. 1145–1154.
KDD-2009-GuoZGZS #semantics #standard: Address standardization with latent semantic association (HG, HZ, ZG, XZ, ZS), pp. 1155–1164.
KDD-2009-GuptaBR #learning: Catching the drift: learning broad matches from clickthrough data (SG, MB, MR), pp. 1165–1174.
KDD-2009-HasanSGA #analysis #named #novel: COA: finding novel patents through text analysis (MAH, WSS, TDG, AA), pp. 1175–1184.
KDD-2009-HiroseYNF #detection #equation #network: Network anomaly detection based on Eigen equation compression (SH, KY, TN, RF), pp. 1185–1194.
KDD-2009-JinHS #machine learning #mining #named #novel #web: OpinionMiner: a novel machine learning system for web opinion mining and extraction (WJ, HHH, RKS), pp. 1195–1204.
KDD-2009-LeeHNW #clustering #query: Query result clustering for object-level search (JL, SwH, ZN, JRW), pp. 1205–1214.
KDD-2009-LiDJEL #random #recommendation: Grocery shopping recommendations based on basket-sensitive random walk (ML, MBD, IHJ, WED, PJGL), pp. 1215–1224.
KDD-2009-LiuKJ #graph #learning #monitoring: Learning dynamic temporal graphs for oil-production equipment monitoring system (YL, JRK, OJ), pp. 1225–1234.
KDD-2009-LuoLXZS #case study #classification #information management #towards #web: Towards combining web classification and web information extraction: a case study (PL, FL, YX, YZ, ZS), pp. 1235–1244.
KDD-2009-MaSSV #detection #learning #web: Beyond blacklists: learning to detect malicious web sites from suspicious URLs (JM, LKS, SS, GMV), pp. 1245–1254.
KDD-2009-MakanjuZM #clustering #using: Clustering event logs using iterative partitioning (AM, ANZH, EEM), pp. 1255–1264.
KDD-2009-McGlohonBASF #detection #graph #named: SNARE: a link analytic system for graph labeling and risk detection (MM, SB, MGA, DMS, CF), pp. 1265–1274.
KDD-2009-MelvilleGL #analysis #classification #sentiment: Sentiment analysis of blogs by combining lexical knowledge with text classification (PM, WG, RDL), pp. 1275–1284.
KDD-2009-MohammedFHL #case study: Anonymizing healthcare data: a case study on the blood transfusion service (NM, BCMF, PCKH, CkL), pp. 1285–1294.
KDD-2009-OzonatY #classification #multi #statistics #towards #web: Towards a universal marketplace over the web: statistical multi-label classification of service provider forms with simulated annealing (KMO, DY), pp. 1295–1304.
KDD-2009-PatnaikMSR #data mining #mining #using: Sustainable operation and management of data center chillers using temporal data mining (DP, MM, RKS, NR), pp. 1305–1314.
KDD-2009-PrakashVAFF #internet #named: BGP-lens: patterns and anomalies in internet routing updates (BAP, NV, DA, MF, CF), pp. 1315–1324.
KDD-2009-SculleyMBB #predict: Predicting bounce rates in sponsored search advertisements (DS, RGM, SB, RJB), pp. 1325–1334.
KDD-2009-SunPLCWLRY #estimation #mining: Mining brain region connectivity for alzheimer’s disease study via sparse inverse covariance estimation (LS, RP, JL, KC, TW, JL, ER, JY), pp. 1335–1344.
KDD-2009-WangCWPBGZ #independence #question: Can we learn a template-independent wrapper for news article extraction from a single training site? (JW, CC, CW, JP, JB, ZG, WVZ), pp. 1345–1354.
KDD-2009-WangWZ #named #quality #ranking #web: PSkip: estimating relevance ranking quality from web search clickthrough data (KW, TW, ZZ), pp. 1355–1364.
KDD-2009-XuYL #mining #using: Named entity mining from click-through data using weakly supervised latent dirichlet allocation (GX, SHY, HL), pp. 1365–1374.
KDD-2009-YangCWHZM #crawling #incremental #web: Incorporating site-level knowledge for incremental crawling of web forums: a list-wise strategy (JMY, RC, CW, HH, LZ, WYM), pp. 1375–1384.
KDD-2009-YeLJHW #detection: Intelligent file scoring system for malware detection from the gray list (YY, TL, QJ, ZH, LW), pp. 1385–1394.
KDD-2009-ZhouJPL #data-driven #framework: OLAP on search logs: an infrastructure supporting data-driven applications in search engines (BZ, DJ, JP, HL), pp. 1395–1404.

John F. Elder IV, Françoise Fogelman-Soulié, Peter A. Flach, Mohammed Javeed ZakiProceedings of the 15th International Conference on Knowledge Discovery and Data MiningKDD, 2009.

Contents (144 items)

John F. Elder IV, Françoise Fogelman-Soulié, Peter A. Flach, Mohammed Javeed Zaki
Proceedings of the 15th International Conference on Knowledge Discovery and Data Mining
KDD, 2009.