7. KDD 2001: San Francisco, CA, USA

• Russ B. Altman:
  Challenges for knowledge discovery in biology. 2
  
• Tom M. Mitchell:
  Extracting targeted data from the web. 3
  
• Raghu Ramakrishnan:
  Mass collaboration and data mining. 4
  
• Nitin Agrarwal:
  Applications of generalized support vector machines to predictive modeling. 6
  
• Herb Edelstein:
  Data mining: are we there yet? 7
  
• Ron Kohavi:
  Mining e-commerce data: the good, the bad, and the ugly. 8-13
  
• Amir Netz:
  Data mining platform for database developers. 14
  
• John Riedl:
  Recommender systems in commerce and community. 15
  
• Zhiqiang Bi, Christos Faloutsos, Flip Korn:
  The "DGX" distribution for mining massive, skewed data. 17-26
  
• Andreas Buja, Yung-Seop Lee:
  Data mining criteria for tree-based regression and classification. 27-36
  
• Igor V. Cadez, Padhraic Smyth, Heikki Mannila:
  Probabilistic modeling of transaction data with applications to profiling, visualization, and prediction. 37-46
  
• Jens-Peter Dittrich, Bernhard Seeger:
  GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces. 47-56
  
• Pedro Domingos, Matthew Richardson:
  Mining the network value of customers. 57-66
  
• William DuMouchel, Daryl Pregibon:
  Empirical bayes screening for multi-item associations. 67-76
  
• Glenn Fung, Olvi L. Mangasarian:
  Proximal support vector machine classifiers. 77-86
  
• Jochen Garcke, Michael Griebel:
  Data mining with sparse grids using simplicial basis functions. 87-96
  
• Geoff Hulten, Laurie Spencer, Pedro Domingos:
  Mining time-changing data streams. 97-106
  
• Eser Kandogan:
  Visualizing multi-dimensional clusters, trends, and outliers using star coordinates. 107-116
  
• Eamonn J. Keogh, Selina Chu, Michael J. Pazzani:
  Ensemble-index: a new approach to indexing large databases. 117-125
  
• Edwin M. Knorr, Raymond T. Ng, Ruben H. Zamar:
  Robust space transformations for distance-based operations. 126-135
  
• Stefan Kramer, Luc De Raedt, Christoph Helma:
  Molecular feature mining in HIV data. 136-143
  
• Bing Liu, Yiming Ma, Philip S. Yu:
  Discovering unexpected information from your competitors' web sites. 144-153
  
• Balaji Padmanabhan, Zhiqiang Zheng, Steven Orla Kimbrough:
  Personalization from incomplete data: what you don't know can hurt. 154-163
  
• Dmitry Pavlov, Padhraic Smyth:
  Probabilistic query models for transaction data. 164-173
  
• David M. Pennock, Steve Lawrence, Finn Årup Nielsen, C. Lee Giles:
  Extracting collective probabilistic forecasts from web games. 174-183
  
• Agma J. M. Traina, Caetano Traina Jr., Spiros Papadimitriou, Christos Faloutsos:
  Tri-plots: scalable tools for multidimensional data mining. 184-193
  
• Cheng Yang, Usama M. Fayyad, Paul S. Bradley:
  Efficient discovery of error-tolerant frequent itemsets in high dimensions. 194-203
  
• Bianca Zadrozny, Charles Elkan:
  Learning and making decisions when costs and probabilities are both unknown. 204-213
  
• Richard Adderley, Peter B. Musgrove:
  Data mining case study: modeling the behavior of offenders who commit serious sexual assaults. 215-220
  
• Charu C. Aggarwal:
  A human-computer cooperative system for effective high dimensional clustering. 221-226
  
• Charu C. Aggarwal, Srinivasan Parthasarathy:
  Mining massively incomplete data sets by conceptual reconstruction. 227-232
  
• Sugato Basu, Raymond J. Mooney, Krupakar V. Pasupuleti, Joydeep Ghosh:
  Evaluating the novelty of text-mined rules using lexical knowledge. 233-238
  
• Alina Beygelzimer, Chang-Shing Perng, Sheng Ma:
  Fast ordering of large categorical datasets for better visualization. 239-244
  
• Ella Bingham, Heikki Mannila:
  Random projection in dimensionality reduction: applications to image and text data. 245-250
  
• Doina Caragea, Dianne Cook, Vasant Honavar:
  Gaining insights into support vector machine pattern classifiers using projection-based tour methods. 251-256
  
• Chien Chin Chen, Meng Chang Chen, Yeali S. Sun:
  PVA: a self-adaptive personal view agent system. 257-262
  
• Tom Chiu, DongPing Fang, John Chen, Yao Wang, Christopher Jeris:
  A robust and scalable clustering algorithm for mixed type attributes in large database environment. 263-268
  
• Inderjit S. Dhillon:
  Co-clustering documents and words using bipartite spectral graph partitioning. 269-274
  
• Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha:
  A spectral method to separate disconnected and nearly-disconnected web graph components. 275-280
  
• David Harel, Yehuda Koren:
  Clustering spatial data using random walks. 281-286
  
• Nitin Indurkhya, Sholom M. Weiss:
  Solving regression problems with rule-based ensemble classifiers. 287-292
  
• Wen Jin, Anthony K. H. Tung, Jiawei Han:
  Mining top-n local outliers in large databases. 293-298
  
• Annaka Kalton, Pat Langley, Kiri Wagstaff, Jungsoon P. Yoo:
  Generalized clustering, supervised learning, and data assignment. 299-304
  
• Diane Lambert, José C. Pinheiro:
  Mining a stream of transactions for customer patterns. 305-310
  
• Aleksandar Lazarevic, Zoran Obradovic:
  The distributed boosting algorithm. 311-316
  
• Dekang Lin, Patrick Pantel:
  Induction of semantic classes from natural language text. 317-322
  
• Dekang Lin, Patrick Pantel:
  DIRT @SBT@discovery of inference rules from text. 323-328
  
• Bing Liu, Wynne Hsu, Yiming Ma:
  Identifying non-actionable association rules. 329-334
  
• Bing Liu, Wynne Hsu, Yiming Ma:
  Discovering the set of fundamental rule changes. 335-340
  
• Heikki Mannila, Marko Salmenkivi:
  Finding simple intensity descriptions from event sequence data. 341-346
  
• Jonathan Moody, Ricardo Bezerra de Andrade e Silva, Joseph Vanderwaart:
  Data filtering for automatic classification of rocks from reflectance spectra. 347-352
  
• Yasuhiko Morimoto:
  Mining frequent neighboring class sets in spatial databases. 353-358
  
• Nikunj C. Oza, Stuart J. Russell:
  Experimental comparisons of online and batch versions of bagging and boosting. 359-364
  
• Petteri Sevon, Hannu Toivonen, Vesa Ollikainen:
  TreeDT: gene mapping by tree disequilibrium test. 365-370
  
• Shashi Shekhar, Chang-Tien Lu, Pusheng Zhang:
  Detecting graph-based spatial outliers: algorithms and applications (a summary of results). 371-376
  
• W. Nick Street, YongSeog Kim:
  A streaming ensemble algorithm (SEA) for large-scale classification. 377-382
  
• Geoffrey I. Webb:
  Discovering associations with numeric variables. 383-388
  
• Kenji Yamanishi, Jun-ichi Takeuchi:
  Discovering outlier filtering rules from unlabeled data: combining a supervised learner with an unsupervised learner. 389-394
  
• Jiong Yang, Wei Wang, Philip S. Yu:
  Infominer: mining surprising periodic patterns. 395-400
  
• Zijian Zheng, Ron Kohavi, Llew Mason:
  Real world performance of association rule algorithms. 401-406
  
• Chidanand Apté, E. Bibelnieks, Ramesh Natarajan, Edwin P. D. Pednault, Fateh Tipu, Deb Campbell, Bryan Nelson:
  Segmentation-based modeling for advanced targeted marketing. 408-413
  
• Pavel Berkhin, Jonathan D. Becher, Dee Jay Randall:
  Interactive path analysis of web site traffic. 414-419
  
• Piew Datta, James Drew, Andrew Betz, D. R. Mani, Jeffery Howard:
  Estimating business targets. 420-425
  
• Charles Elkan:
  Magical thinking in data mining: lessons from CoIL challenge 2000. 426-431
  
• Edgar Hotz, Udo Grimmer, W. Heuser, Gholamreza Nakhaeizadeh, M. Wieczorek:
  REVI-MINER, a KDD-environment for deviation detection and analysis of warranty and goodwill cost statements in automotive industry. 432-437
  
• Christoph Hueglin, Francesco Vannotti:
  Data mining techniques to improve forecast accuracy in airline business. 438-442
  
• Hang Li, Kenji Yamanishi:
  Mining from open answers in questionnaire data. 443-449
  
• Teresa Mah, Hank Hoek, Ying Li:
  Funnel report mining for the MSN network. 450-455
  
• Saharon Rosset, Einat Neumann, Uri Eick, Nurit Vatnik, Yizhak Idan:
  Evaluation of prediction models for marketing campaigns. 456-461
  
• W. Scott Spangler, Jeffrey T. Kreulen:
  Knowledge base maintenance using knowledge gap analysis. 462-466
  
• Doug Warner, J. Neal Richter, Stephen D. Durbin, Bikramjit Banerjee:
  Mining user session data to facilitate user interaction with a customer service knowledge base in RightNow Web. 467-472
  
• Qiang Yang, Henry Haining Zhang, Ian Tian Yi Li:
  Mining web logs for prediction models in WWW caching and prefetching. 473-478
  

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