Robert Grossman, Roberto J. Bayardo, Kristin P. Bennett
Proceedings of the 11th International Conference on Knowledge Discovery and Data Mining
KDD, 2005.

@proceedings{KDD-2005,
	address       = "Chicago, Illinois, USA",
	editor        = "Robert Grossman and Roberto J. Bayardo and Kristin P. Bennett",
	isbn          = "1-59593-135-X",
	publisher     = "{ACM}",
	title         = "{Proceedings of the 11th International Conference on Knowledge Discovery and Data Mining}",
	year          = 2005,
}

Contents (104 items)

24 ×#mining
14 ×#clustering
8 ×#using
7 ×#detection
7 ×#graph
7 ×#network
7 ×#performance
6 ×#classification
6 ×#learning
6 ×#predict

KDD-2005-Raghavan #network

Incentive networks (PR), p. 1.

KDD-2005-Fulgoni #internet #mining

Mining the internet: the eighth wonder of the world (GF), p. 2.

KDD-2005-Barabasi #architecture #complexity #network #web

The architecture of complexity: the structure and the dynamics of networks, from the web to the cell (ALB), p. 3.

KDD-2005-ChenH #analysis #classification #image #network

A Bayesian network classifier with inverse tree structure for voxelwise magnetic resonance image analysis (RC, EH), pp. 4–12.

KDD-2005-DasguptaKRT #semantics

Variable latent semantic indexing (AD, RK, PR, AT), pp. 13–21.

KDD-2005-FanLH #image #learning #mining #semantics #statistics

Mining images on semantics via statistical learning (JF, HL, MSH), pp. 22–31.

KDD-2005-FungSR #linear

Rule extraction from linear support vector machines (GF, SS, RBR), pp. 32–40.

KDD-2005-GaoLZCM #clustering #consistency #graph #higher-order #semistructured data

Consistent bipartite graph co-partitioning for star-structured high-order heterogeneous data co-clustering (BG, TYL, XZ, QC, WYM), pp. 41–50.

KDD-2005-GionisHPT #clustering

Dimension induced clustering (AG, AH, SP, PT), pp. 51–60.

KDD-2005-GoethalsHB #graph #mining #query

Mining tree queries in a graph (BG, EH, JVdB), pp. 61–69.

KDD-2005-GondekH #clustering

Non-redundant clustering with conditional ensembles (DG, TH), pp. 70–77.

KDD-2005-GruhlGKNT #online #power of #predict

The predictive power of online chatter (DG, RVG, RK, JN, AT), pp. 78–87.

KDD-2005-GuhaH #data type #fault

Wavelet synopsis for data streams: minimizing non-euclidean error (SG, BH), pp. 88–97.

KDD-2005-HershkopS #email #modelling #reduction

Combining email models for false positive reduction (SH, SJS), pp. 98–107.

KDD-2005-JakulinMDBZ #visualisation

Nomograms for visualizing support vector machines (AJ, MM, JD, IB, BZ), pp. 108–117.

KDD-2005-JaroszewiczS #network #performance

Fast discovery of unexpected patterns in data, relative to a Bayesian network (SJ, TS), pp. 118–127.

KDD-2005-Kolcz #classification #naive bayes

Local sparsity control for naive Bayes with extreme misclassification costs (AK), pp. 128–137.

KDD-2005-KubicaMCJ #algorithm #multi #performance

A multiple tree algorithm for the efficient association of asteroid observations (JK, AWM, AJC, RJ), pp. 138–146.

KDD-2005-LangeB #probability

Combining partitions by probabilistic label aggregation (TL, JMB), pp. 147–156.

KDD-2005-LazarevicK #detection

Feature bagging for outlier detection (AL, VK), pp. 157–166.

KDD-2005-LebanMBZ #effectiveness #modelling #visual notation

Simple and effective visual models for gene expression cancer diagnostics (GL, MM, IB, BZ), pp. 167–176.

KDD-2005-LeskovecKF #graph

Graphs over time: densification laws, shrinking diameters and possible explanations (JL, JMK, CF), pp. 177–187.

KDD-2005-Li #clustering

A general model for clustering binary data (TL), pp. 188–197.

KDD-2005-MeiZ #mining

Discovering evolutionary theme patterns from text: an exploration of temporal text mining (QM, CZ), pp. 198–207.

KDD-2005-MeruguG #data flow #distributed #framework #learning #semistructured data

A distributed learning framework for heterogeneous data sources (SM, JG), pp. 208–217.

KDD-2005-NeillMSD #clustering #detection

Detection of emerging space-time clusters (DBN, AWM, MS, KD), pp. 218–227.

KDD-2005-PeiJZ #clique #mining #on the

On mining cross-graph quasi-cliques (JP, DJ, AZ), pp. 228–238.

KDD-2005-RadlinskiJ #feedback #learning #query #rank

Query chains: learning to rank from implicit feedback (FR, TJ), pp. 239–248.

KDD-2005-Rosset #robust

Robust boosting and its relation to bagging (SR), pp. 249–255.

KDD-2005-Sandler #classification #linear #on the #programming #using

On the use of linear programming for unsupervised text classification (MS), pp. 256–264.

KDD-2005-Scholz #mining

Sampling-based sequential subgroup mining (MS), pp. 265–274.

KDD-2005-SilvaZS #mining #probability #workflow

Probabilistic workflow mining (RBdAeS, JZ, JGS), pp. 275–284.

KDD-2005-UkkonenFM #partial order

Finding partial orders from unordered 0-1 data (AU, MF, HM), pp. 285–293.

KDD-2005-WangLLMZ #using #web

Web object indexing using domain knowledge (MW, ZL, LL, WYM, NZ), pp. 294–303.

KDD-2005-PhanNHH #learning

Improving discriminative sequential learning with rare--but--important associations (XHP, MLN, TBH, SH), pp. 304–313.

KDD-2005-YanCHX #approach

Summarizing itemset patterns: a profile-based approach (XY, HC, JH, DX), pp. 314–323.

KDD-2005-YanZH #constraints #graph #mining #relational

Mining closed relational graphs with connectivity constraints (XY, XJZ, JH), pp. 324–333.

KDD-2005-YangZW

Anonymity-preserving data collection (ZY, SZ, RNW), pp. 334–343.

KDD-2005-YinHY #clustering

Cross-relational clustering with user’s guidance (XY, JH, PSY), pp. 344–353.

KDD-2005-Yu #ranking #retrieval

SVM selective sampling for ranking with application to data retrieval (HY), pp. 354–363.

KDD-2005-ZakiR #mining #reasoning #set #using

Reasoning about sets using redescription mining (MJZ, NR), pp. 364–373.

KDD-2005-ZhangWZ #classification #privacy

A new scheme on privacy-preserving data classification (NZ, SW, WZ), pp. 374–383.

KDD-2005-ZhouFSU #feature model #streaming #using

Streaming feature selection using alpha-investing (JZ, DPF, RAS, LHU), pp. 384–393.

KDD-2005-FormanEC #documentation #repository #scalability

Finding similar files in large document repositories (GF, KE, SC), pp. 394–400.

KDD-2005-FujimakiYM #approach #detection #kernel #problem #using

An approach to spacecraft anomaly detection problem using kernel feature space (RF, TY, KM), pp. 401–410.

KDD-2005-Ghani #online #predict

Price prediction and insurance for online auctions (RG), pp. 411–418.

KDD-2005-GlanceHNSST #online

Deriving marketing intelligence from online discussion (NSG, MH, KN, MS, RS, TT), pp. 419–428.

KDD-2005-HeC #approach #robust

Making holistic schema matching robust: an ensemble approach (BH, KCCC), pp. 429–438.

KDD-2005-NasraouiCR #metric #mining #retrieval #similarity #using #web

Using retrieval measures to assess similarity in mining dynamic web clickstreams (ON, CC, CR), pp. 439–448.

KDD-2005-NevilleSJKPG #information management #relational #using

Using relational knowledge discovery to prevent securities fraud (JN, ÖS, DJ, JK, KP, HGG), pp. 449–458.

KDD-2005-NorenOB #database #detection #safety

A hit-miss model for duplicate detection in the WHO drug safety database (GNN, RO, AB), pp. 459–468.

KDD-2005-RaskuttiH #predict

Predicting the product purchase patterns of corporate customers (BR, AH), pp. 469–478.

KDD-2005-SongLTS #behaviour #modelling #predict

Modeling and predicting personal information dissemination behavior (XS, CYL, BLT, MTS), pp. 479–488.

KDD-2005-TangLCT #email

Email data cleaning (JT, HL, YC, ZT), pp. 489–498.

KDD-2005-YamanishiM #mining #monitoring #network

Dynamic syslog mining for network failure monitoring (KY, YM), pp. 499–508.

KDD-2005-YanFB #constraints #industrial

Enhancing the lift under budget constraints: an application in the mutual fund industry (LY, MF, PB), pp. 509–515.

KDD-2005-YangL #learning #predict

Learning to predict train wheel failures (CY, SL), pp. 516–525.

KDD-2005-Aggarwal #algorithm #classification #towards

Towards exploratory test instance specific algorithms for high dimensional classification (CCA), pp. 526–531.

KDD-2005-BanerjeeKGBM #clustering #modelling

Model-based overlapping clustering (AB, CK, JG, SB, RJM), pp. 532–537.

KDD-2005-BesemannD #integration #markov #mining

Integration of profile hidden Markov model output into association rule mining (CB, AD), pp. 538–543.

KDD-2005-CareniniNZ #email #scalability

Scalable discovery of hidden emails from large folders (GC, RTN, XZ), pp. 544–549.

KDD-2005-ChenW #mining #web

Web mining from competitors’ websites (XC, YfBW), pp. 550–555.

KDD-2005-ChenCC #adaptation #detection #named

LIPED: HMM-based life profiles for adaptive event detection (CCC, MCC, MSC), pp. 556–561.

KDD-2005-CongHP #mining #parallel

Parallel mining of closed sequential patterns (SC, JH, DAP), pp. 562–567.

KDD-2005-FastJL #network #peer-to-peer #social

Creating social networks to improve peer-to-peer networking (ASF, DJ, BNL), pp. 568–573.

KDD-2005-GuhaKSS #documentation #weaving #web

Unweaving a web of documents (RVG, RK, DS, RS), pp. 574–579.

KDD-2005-HeerenP

Maximal boasting (CH, LP), pp. 580–585.

KDD-2005-ItoSKM #analysis #kernel

Application of kernels to link analysis (TI, MS, TK, YM), pp. 586–592.

KDD-2005-JagannathanW #clustering #distributed #privacy

Privacy-preserving distributed k-means clustering over arbitrarily partitioned data (GJ, RNW), pp. 593–599.

KDD-2005-JinSA #information management #mining #optimisation

Simultaneous optimization of complex mining tasks with a knowledgeable cache (RJ, KS, GA), pp. 600–605.

KDD-2005-JinWPPA #dataset #graph

Discovering frequent topological structures from graph datasets (RJ, CW, DP, SP, GA), pp. 606–611.

KDD-2005-JinZM #collaboration #recommendation #web

A maximum entropy web recommendation system: combining collaborative and content features (XJ, YZ, BM), pp. 612–617.

KDD-2005-KawamaeT #collaboration #information retrieval #semantics

Information retrieval based on collaborative filtering with latent interest semantic map (NK, KT), pp. 618–623.

KDD-2005-KoppelSZ #fault #mining

Determining an author’s native language by mining a text for errors (MK, JS, KZ), pp. 624–628.

KDD-2005-DhillonGK #algorithm #clustering #graph #kernel #multi #performance

A fast kernel-based multilevel algorithm for graph clustering (ISD, YG, BK), pp. 629–634.

KDD-2005-LongZY #clustering #composition

Co-clustering by block value decomposition (BL, Z(Z, PSY), pp. 635–640.

KDD-2005-LowdM #learning

Adversarial learning (DL, CM), pp. 641–647.

KDD-2005-ManeSH #classification #independence #using

Estimating missed actual positives using independent classifiers (SM, JS, SYH), pp. 648–653.

KDD-2005-Momma #kernel #performance #scalability

Efficient computations via scalable sparse kernel partial least squares and boosted latent features (MM), pp. 654–659.

KDD-2005-MorchenU #information management #optimisation

Optimizing time series discretization for knowledge discovery (FM, AU), pp. 660–665.

KDD-2005-MorinagaAISA #dependence #mining #semantics

Key semantics extraction by dependency tree mining (SM, HA, TI, YS, SA), pp. 666–671.

KDD-2005-KriegelP #clustering #nondeterminism

Density-based clustering of uncertain data (HPK, MP), pp. 672–677.

KDD-2005-SpertusSB #metric #network #scalability #similarity #social

Evaluating similarity measures: a large-scale study in the orkut social network (ES, MS, OB), pp. 678–684.

KDD-2005-SurdeanuTA #approach #clustering #documentation #hybrid

A hybrid unsupervised approach for document clustering (MS, JT, AA), pp. 685–690.

KDD-2005-TaoZ #corpus #integration #mining

Mining comparable bilingual text corpora for cross-language information integration (TT, CZ), pp. 691–696.

KDD-2005-Torgo #fault

Regression error characteristic surfaces (LT), pp. 697–702.

KDD-2005-WuCP #distance #kernel

Formulating distance functions via the kernel trick (GW, EYC, NP), pp. 703–709.

KDD-2005-YangWZ #data type #predict

Combining proactive and reactive predictions for data streams (YY, XW, XZ), pp. 710–715.

KDD-2005-YangPM #framework #mining

A generalized framework for mining spatio-temporal patterns in scientific data (HY, SP, SM), pp. 716–721.

KDD-2005-Yang #graph

Building connected neighborhood graphs for isometric data embedding (LY), pp. 722–728.

KDD-2005-ZaianeE #traversal

Pattern lattice traversal by selective jumps (ORZ, MEH), pp. 729–735.

KDD-2005-ZakiPAS #algorithm #category theory #clustering #dataset #effectiveness #mining #named

CLICKS: an effective algorithm for mining subspace clusters in categorical datasets (MJZ, MP, IA, TS), pp. 736–742.

KDD-2005-ColeSZ #correlation #performance

Fast window correlations over uncooperative time series (RC, DS, XZ), pp. 743–749.

KDD-2005-ChenJUY #component #detection #locality #online

Failure detection and localization in component based systems by online tracking (HC, GJ, CU, KY), pp. 750–755.

KDD-2005-JeskeSLYCXYLHR #generative #information management #set

Generation of synthetic data sets for evaluating the accuracy of knowledge discovery systems (DRJ, BS, PJL, LY, SC, RX, TY, ML, DH, RR), pp. 756–762.

KDD-2005-KalosR #data mining #industrial #mining

Data mining in the chemical industry (ANK, TR), pp. 763–769.

KDD-2005-LiFHCJMWSK #mining

Mining risk patterns in medical data (JL, AWCF, HH, JC, HJ, DM, GJW, RS, CK), pp. 770–775.

KDD-2005-LiLMP #framework #mining

An integrated framework on mining logs files for computing system management (TL, FL, SM, WP), pp. 776–781.

KDD-2005-LiRGMAEGATJ #automation #detection

Automated detection of frontal systems from numerical model-generated data (XL, RR, SJG, SM, BA, DE, SG, RA, JT, JCJ), pp. 782–787.

KDD-2005-PearsonKH #database #modelling

Disease progression modeling from historical clinical databases (RKP, RJK, AH), pp. 788–793.

KDD-2005-Petrushin #mining #multi #self #using #video

Mining rare and frequent events in multi-camera surveillance video using self-organizing maps (VAP), pp. 794–800.

KDD-2005-PowersGC #enterprise #performance

Short term performance forecasting in enterprise systems (RP, MG, IC), pp. 801–807.

KDD-2005-SanghaiSDK #architecture #clustering #design #multi #performance #simulation

A multinomial clustering model for fast simulation of computer architecture designs (KS, TS, JGD, DRK), pp. 808–813.

KDD-2005-WangPY #array #similarity

Pattern-based similarity search for microarray data (HW, JP, PSY), pp. 814–819.