8. KDD 2002:
Edmonton,
Alberta,
Canada
Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, July 23-26, 2002, Edmonton, Alberta, Canada.
ACM 2002, ISBN 1-58113-567-X 
@proceedings{DBLP:conf/kdd/2002,
title = {Proceedings of the Eighth ACM SIGKDD International Conference
on Knowledge Discovery and Data Mining, July 23-26, 2002, Edmonton,
Alberta, Canada},
booktitle = {KDD},
publisher = {ACM},
year = {2002},
isbn = {1-58113-567-X},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
Statistical methods I
Frequent patterns I
Graphs and trees
Streams and time series
Visualization
Web search and navigation
Sequences and strings
Statistical methods II
Text classification
Frequent patterns II
Web page classification
Learning methods
Intrusion and privacy
Ensembles and boosting
Industry track papers
- Mohammad El-Ramly, Eleni Stroulia, Paul G. Sorenson:
From run-time behavior to usage scenarios: an interaction-pattern mining approach.
315-324
- Andrew Storey, Marc-David Cohen:
Exploiting response models: optimizing cross-sell and up-sell opportunities in banking.
325-331
- Saharon Rosset, Einat Neumann, Uri Eick, Nurit Vatnik, Yizhak Idan:
Customer lifetime value modeling and its use for customer retention planning.
332-340
- Satoshi Morinaga, Kenji Yamanishi, Kenji Tateishi, Toshikazu Fukushima:
Mining product reputations on the Web.
341-349
- Sheila Tejada, Craig A. Knoblock, Steven Minton:
Learning domain-independent string transformation weights for high accuracy object identification.
350-359
- Sholom M. Weiss, Naval K. Verma:
A system for real-time competitive market intelligence.
360-365
- Klaus Julisch, Marc Dacier:
Mining intrusion detection alarms for actionable knowledge.
366-375
- Matthew V. Mahoney, Philip K. Chan:
Learning nonstationary models of normal network traffic for detecting novel attacks.
376-385
- Karlton Sequeira, Mohammed Javeed Zaki:
ADMIT: anomaly-based data mining for intrusions.
386-395
- Alexander Tuzhilin, Gediminas Adomavicius:
Handling very large numbers of association rules in the analysis of microarray data.
396-404
- Peter Antal, Patrick Glenisson, Geert Fannes:
On the potential of domain literature for clustering and Bayesian network learning.
405-414
- Yulan Liang, Arpad Kelemen:
Mining heterogeneous gene expression data with time lagged recurrent neural networks.
415-421
Poster papers
- Charu C. Aggarwal:
Collaborative crawling: mining user experiences for topical resource discovery.
423-428
- Jay Ayres, Jason Flannick, Johannes Gehrke, Tomi Yiu:
Sequential PAttern mining using a bitmap representation.
429-435
- Florian Beil, Martin Ester, Xiaowei Xu:
Frequent term-based text clustering.
436-442
- Shai Ben-David, Johannes Gehrke, Reba Schuller:
A theoretical framework for learning from a pool of disparate data sources.
443-449
- Ella Bingham, Heikki Mannila, Jouni K. Seppänen:
Topics in 0--1 data.
450-455
- Olcay Boz:
Extracting decision trees from trained neural networks.
456-461
- Bin Chen, Peter J. Haas, Peter Scheuermann:
A new two-phase sampling based algorithm for discovering association rules.
462-468
- Christina Yip Chung, Bin Chen:
CVS: a Correlation-Verification based Smoothing technique on information retrieval and term clustering.
469-474
- William W. Cohen, Jacob Richman:
Learning to match and cluster large high-dimensional data sets for data integration.
475-480
- Alin Dobra, Johannes Gehrke:
SECRET: a scalable linear regression tree algorithm.
481-487
- Tina Eliassi-Rad, Terence Critchlow, Ghaleb Abdulla:
Tina Eliassi-Rad, Terence Critchlow, Ghaleb Abdulla.
488-494
- Bin Fang, Wynne Hsu, Mong-Li Lee:
Tumor cell identification using features rules.
495-500
- Dimitris Fragoudis, Dimitris Meretakis, Spiros Likothanassis:
Integrating feature and instance selection for text classification.
501-506
- Hichem Frigui:
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets.
507-512
- Shantanu Godbole, Sunita Sarawagi, Soumen Chakrabarti:
Scaling multi-class support vector machines using inter-class confusion.
513-518
- Tu Bao Ho, Trong Dung Nguyen, DucDung Nguyen:
Visualization support for a user-centered KDD process.
519-524
- Geoff Hulten, Pedro Domingos:
Mining complex models from arbitrarily large databases in constant time.
525-531
- Srinivasan Jagannathan, Jayanth Nayak, Kevin C. Almeroth, Markus Hofmann:
A model for discovering customer value for E-content.
532-537
- Glen Jeh, Jennifer Widom:
SimRank: a measure of structural-context similarity.
538-543
- Xiaoming Jin, Yuchang Lu, Chunyi Shi:
Similarity measure based on partial information of time series.
544-549
- Eamonn J. Keogh, Stefano Lonardi, Bill Yuan-chi Chiu:
Finding surprising patterns in a time series database in linear time and space.
550-556
- Mahesh Kumar, Nitin R. Patel, Jonathan Woo:
Clustering seasonality patterns in the presence of errors.
557-563
- Jiuyong Li, Rodney W. Topor, Hong Shen:
Construct robust rule sets for classification.
564-569
- Ruey-Hsia Li, Geneva G. Belford:
Instability of decision tree classification algorithms.
570-575
- Cheng-Ru Lin, Chang-Hung Lee, Ming-Syan Chen, Philip S. Yu:
Distributed data mining in a chain store database of short transactions.
576-581
- Cheng-Ru Lin, Ming-Syan Chen:
A robust and efficient clustering algorithm based on cohesion self-merging.
582-587
- Shian-Hua Lin, Jan-Ming Ho:
Discovering informative content blocks from Web documents.
588-593
- Bertis B. Little, Walter L. Johnston, Ashley C. Lovell, Roderick M. Rejesus, Steve A. Steed:
Collusion in the U.S. crop insurance program: applied data mining.
594-598
- Rey-Long Liu, Yun-Ling Lu:
Incremental context mining for adaptive document classification.
599-604
- Anna Olecka:
Evaluating classifiers' performance in a constrained environment.
605-612
- Patrick Pantel, Dekang Lin:
Discovering word senses from text.
613-619
- Bhavani Raskutti, Herman L. Ferrá, Adam Kowalczyk:
Combining clustering and co-training to enhance text classification using unlabelled data.
620-625
- Naonori Ueda, Kazumi Saito:
Single-shot detection of multiple categories of text using parametric mixture models.
626-631
- Secil Ugurel, Robert Krovetz, C. Lee Giles:
What's the code?: automatic classification of source code archives.
639-644
- Jaideep Vaidya, Chris Clifton:
Privacy preserving association rule mining in vertically partitioned data.
639-644
- Michail Vlachos, Carlotta Domeniconi, Dimitrios Gunopulos, George Kollios, Nick Koudas:
Non-linear dimensionality reduction techniques for classification and visualization.
645-651
- Ke Wang, Ming-Yen Thomas Su:
Item selection by "hub-authority" profit ranking.
652-657
- Vasa Curcin, Moustafa Ghanem, Yike Guo, Martin Köhler, Anthony Rowe, Jameel Syed, Patrick Wendel:
Discovery net: towards a grid of knowledge discovery.
658-663
- Leejay Wu, Christos Faloutsos:
Making every bit count: fast nonlinear axis scaling.
664-669
- Xintao Wu, Jianping Fan, Kalpathi R. Subramanian:
B-EM: a classifier incorporating bootstrap with EM approach for data mining.
670-675
- Kenji Yamanishi, Jun-ichi Takeuchi:
A unifying framework for detecting outliers and change points from non-stationary time series data.
676-681
- Yiling Yang, Xudong Guan, Jinyuan You:
CLOPE: a fast and effective clustering algorithm for transactional data.
682-687
- Yiming Yang, Jian Zhang, Jaime G. Carbonell, Chun Jin:
Topic-conditioned novelty detection.
688-693
- Bianca Zadrozny, Charles Elkan:
Transforming classifier scores into accurate multiclass probability estimates.
694-699
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