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

Raghu Ramakrishnan, Salvatore J. Stolfo, Roberto J. Bayardo, Ismail Parsa
Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining
KDD, 2000.

KER

@proceedings{KDD-2000,
	acmid         = "347090",
	address       = "Boston, Massachusetts, USA",
	editor        = "Raghu Ramakrishnan and Salvatore J. Stolfo and Roberto J. Bayardo and Ismail Parsa",
	isbn          = "1-58113-233-6",
	publisher     = "{ACM}",
	title         = "{Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining}",
	year          = 2000,
}

Contents (75 items)

KDD-2000-Papadimitriou #data mining #mining #on the: On certain rigorous approaches to data mining (CHP), p. 2.
KDD-2000-Buchanan #information management #source code #using: Informed knowledge discovery: using prior knowledge in discovery programs (BGB), p. 3.
KDD-2000-Catlett #data mining #mining #privacy: Among those dark electronic mills: privacy and data mining (JC), p. 4.
KDD-2000-Goodnight: Decision support in the booming e-world (JG), p. 5.
KDD-2000-Cutler #metric #named: E-metrics: tomorrow’s business metrics today (MC), p. 6.
KDD-2000-Stodder #data mining #mining: After the gold rush (invited talk, abstract only): data mining in the new economy (DS), p. 7.
KDD-2000-CortesFPR #data type #named: Hancock: a language for extracting signatures from data streams (CC, KF, DP, AR), pp. 9–17.
KDD-2000-FountainDS #mining #testing: Mining IC test data to optimize VLSI testing (TF, TGD, BS), pp. 18–25.
KDD-2000-TalbertF #analysis #empirical: An empirical analysis of techniques for constructing and searching k-dimensional trees (DAT, DHF), pp. 26–33.
KDD-2000-Zaki #generative: Generating non-redundant association rules (MJZ), pp. 34–43.
KDD-2000-Senator #case study #detection #information management #scalability: Ongoing management and application of discovered knowledge in a large regulatory organization: a case study of the use and impact of NASD Regulation’s Advanced Detection System (RADS) (TES), pp. 44–53.
KDD-2000-PadmanabhanT #set: Small is beautiful: discovering the minimal set of unexpected patterns (BP, AT), pp. 54–63.
KDD-2000-FungM #classification: Data selection for support vector machine classifiers (GF, OLM), pp. 64–70.
KDD-2000-DomingosH #data type #mining #performance: Mining high-speed data streams (PMD, GH), pp. 71–80.
KDD-2000-GeS #markov #pattern matching: Deformable Markov model templates for time-series pattern matching (XG, PS), pp. 81–90.
KDD-2000-IyengarAZ #adaptation #learning #using: Active learning using adaptive resampling (VSI, CA, TZ), pp. 91–98.
KDD-2000-Webb #performance: Efficient search for association rules (GIW), pp. 99–107.
KDD-2000-AgarwalAP #generative: Depth first generation of long patterns (RCA, CCA, VVVP), pp. 108–118.
KDD-2000-AggarwalY #similarity: The IGrid index: reversing the dimensionality curse for similarity indexing in high dimensional space (CCA, PSY), pp. 119–129.
KDD-2000-Tresp: The generalized Bayesian committee machine (VT), pp. 130–139.
KDD-2000-CadezGS #clustering #framework #probability: A general probabilistic framework for clustering individuals and objects (IVC, SG, PS), pp. 140–149.
KDD-2000-FlakeLG #community #identification #performance #web: Efficient identification of Web communities (GWF, SL, CLG), pp. 150–160.
KDD-2000-MannilaM #partial order: Global partial orders from sequential data (HM, CM), pp. 161–168.
KDD-2000-McCallumNU #clustering #performance #set: Efficient clustering of high-dimensional data sets with application to reference matching (AM, KN, LHU), pp. 169–178.
KDD-2000-AnkerstEK #classification #effectiveness #towards: Towards an effective cooperation of the user and the computer for classification (MA, ME, HPK), pp. 179–188.
KDD-2000-FeldmanLRSS #approximate #bias #framework #information management #specification: A framework for specifying explicit bias for revision of approximate information extraction rules (RF, YL, BR, YS, JS), pp. 189–197.
KDD-2000-DrummondH #representation: Explicitly representing expected cost: an alternative to ROC representation (CD, RCH), pp. 198–207.
KDD-2000-LiuHH #multi #summary: Multi-level organization and summarization of the discovered rules (BL, MH, WH), pp. 208–217.
KDD-2000-CrapoWWW #modelling #perspective #process #visualisation: Visualization and the process of modeling: a cognitive-theoretic view (AWC, LBW, WAW, TRW), pp. 218–226.
KDD-2000-HofmannSW #interactive #visualisation: Visualizing association rules with interactive mosaic plots (HH, AS, AFXW), pp. 227–235.
KDD-2000-Yang #3d #dataset #interactive #relational #scalability: Interactive exploration of very large relational datasets through 3D dynamic projections (LY), pp. 236–243.
KDD-2000-HanC #information management #named #process #visualisation: RuleViz: a model for visualizing knowledge discovery process (JH, NC), pp. 244–253.
KDD-2000-CohenKM: Hardening soft information sources (WWC, HAK, DAM), pp. 255–259.
KDD-2000-BarbaraC #clustering #dataset #using: Using the fractal dimension to cluster datasets (DB, PC), pp. 260–264.
KDD-2000-WangZH: Growing decision trees on support-less association rules (KW, SZ, YH), pp. 265–269.
KDD-2000-WangYY #mining #performance: Efficient mining of weighted association rules (WAR) (WW, JY, PSY), pp. 270–274.
KDD-2000-YangWY #mining: Mining asynchronous periodic patterns in time series data (JY, WW, PSY), pp. 275–279.
KDD-2000-CadezHMSW #clustering #modelling #navigation #using #visualisation #web: Visualization of navigation patterns on a Web site using model-based clustering (IVC, DH, CM, PS, SW), pp. 280–284.
KDD-2000-KeoghP #scalability: Scaling up dynamic time warping for datamining applications (EJK, MJP), pp. 285–289.
KDD-2000-LeeLL #knowledge-based #named: IntelliClean: a knowledge-based intelligent data cleaner (MLL, TWL, WLL), pp. 290–294.
KDD-2000-PavlovCS #scalability #towards #using: Towards scalable support vector machines using squashing (DP, DC, PS), pp. 295–299.
KDD-2000-BrijsGSVW #data mining #framework #mining: A data mining framework for optimal product selection in retail supermarket data: the generalized PROFSET model (TB, BG, GS, KV, GW), pp. 300–304.
KDD-2000-WangMSW #biology #case study #classification #data mining #mining #network #sequence: Application of neural networks to biological data mining: a case study in protein sequence classification (JTLW, QM, DS, CHW), pp. 305–309.
KDD-2000-ZhangDR #constraints #dataset #scalability: Exploring constraints to efficiently mine emerging patterns from large high-dimensional datasets (XZ, GD, KR), pp. 310–314.
KDD-2000-Bay #mining #multi #set: Multivariate discretization of continuous variables for set mining (SDB), pp. 315–319.
KDD-2000-YamanishiTWM #algorithm #detection #finite #learning #online #using: On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms (KY, JiT, GJW, PM), pp. 320–324.
KDD-2000-KontkanenLMT #visualisation: Unsupervised Bayesian visualization of high-dimensional data (PK, JL, PM, HT), pp. 325–329.
KDD-2000-SchefferW #algorithm: A sequential sampling algorithm for a general class of utility criteria (TS, SW), pp. 330–334.
KDD-2000-GarofalakisHRS #algorithm #constraints #performance: Efficient algorithms for constructing decision trees with constraints (MNG, DH, RR, KS), pp. 335–339.
KDD-2000-YiS #classification #documentation: A classifier for semi-structured documents (JY, NS), pp. 340–344.
KDD-2000-DeCosteW: Alpha seeding for support vector machines (DD, KW), pp. 345–349.
KDD-2000-PeiH #constraints #mining #question: Can we push more constraints into frequent pattern mining? (JP, JH), pp. 350–354.
KDD-2000-HanPMCDH #mining #named: FreeSpan: frequent pattern-projected sequential pattern mining (JH, JP, BMA, QC, UD, MH), pp. 355–359.
KDD-2000-DyB #feature model #interactive #visualisation: Visualization and interactive feature selection for unsupervised data (JGD, CEB), pp. 360–364.
KDD-2000-KimSM #feature model #learning #search-based: Feature selection in unsupervised learning via evolutionary search (YK, WNS, FM), pp. 365–369.
KDD-2000-InselbergA #classification #visualisation: Classification and visualization for high-dimensional data (AI, TA), pp. 370–374.
KDD-2000-GardnerB #data mining #mining #problem: Data mining solves tough semiconductor manufacturing problems (MG, JB), pp. 376–383.
KDD-2000-KingKCD #data mining #functional #mining #predict #sequence #using: Genome scale prediction of protein functional class from sequence using data mining (RDK, AK, AC, LD), pp. 384–389.
KDD-2000-PenaFL #behaviour #data mining #detection #mining: Data mining to detect abnormal behavior in aerospace data (JMP, FF, SL), pp. 390–397.
KDD-2000-GerstenWA #case study #experience #modelling #predict #roadmap #tool support: Predictive modeling in automotive direct marketing: tools, experiences and open issues (WG, RW, DA), pp. 398–406.
KDD-2000-BeefermanB #clustering #query: Agglomerative clustering of a search engine query log (DB, ALB), pp. 407–416.
KDD-2000-TanBHG #data mining #mining: Textual data mining of service center call records (PNT, HB, SAH, RPG), pp. 417–423.
KDD-2000-BecherBF #automation #data analysis #data mining #mining #performance: Automating exploratory data analysis for efficient data mining (JDB, PB, EF), pp. 424–429.
KDD-2000-HsuLLL #database #mining: Exploration mining in diabetic patients databases: findings and conclusions (WH, MLL, BL, TWL), pp. 430–436.
KDD-2000-KittsFV #independence #named #performance #recommendation: Cross-sell: a fast promotion-tunable customer-item recommendation method based on conditionally independent probabilities (BK, DF, MV), pp. 437–446.
KDD-2000-ChouGGK #identification: Identifying prospective customers (PBC, EG, DG, PK), pp. 447–456.
KDD-2000-MaLWYL #data mining #mining #student #using: Targeting the right students using data mining (YM, BL, CKW, PSY, SML), pp. 457–464.
KDD-2000-Bhattacharyya #algorithm #data mining #mining #modelling #multi #performance: Evolutionary algorithms in data mining: multi-objective performance modeling for direct marketing (SB), pp. 465–473.
KDD-2000-Farahat #hybrid #process: Hybrid Poisson process (AF), pp. 474–479.
KDD-2000-DhondGV #data mining #mining #optimisation: Data mining techniques for optimizing inventories for electronic commerce (AD, AG, SV), pp. 480–486.
KDD-2000-GavrilovAIM #mining #question: Mining the stock market (extended abstract): which measure is best? (MG, DA, PI, RM), pp. 487–496.
KDD-2000-Caraca-ValenteL: Discovering similar patterns in time series (JPCV, ILC), pp. 497–505.
KDD-2000-RaghavanBS #detection #predict #process #using: Defection detection: using activity profiles to predict ISP customer vulnerability (NR, RMB, MS), pp. 506–515.
KDD-2000-ChenLP #estimation #incremental: Incremental quantile estimation for massive tracking (FC, DL, JCP), pp. 516–522.
KDD-2000-PairceirMS #database #distributed #exception #multi: Discovery of multi-level rules and exceptions from a distributed database (RP, SIM, BWS), pp. 523–532.

Raghu Ramakrishnan, Salvatore J. Stolfo, Roberto J. Bayardo, Ismail ParsaProceedings of the Sixth International Conference on Knowledge Discovery and Data MiningKDD, 2000.

Contents (75 items)

Raghu Ramakrishnan, Salvatore J. Stolfo, Roberto J. Bayardo, Ismail Parsa
Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining
KDD, 2000.