1. ICDM 2001: San Jose, California, USA

Regular Papers

• Charu C. Aggarwal, Philip S. Yu:
  On Effective Conceptual Indexing and Similarity Search in Text Data. 3-10
  
• Aijun An, Yuanyuan Wang:
  Comparisons of Classification Methods for Screening Potential Compounds. 11-18
  
• Michael Anderson:
  Knowledge Discovery from Diagrammatically Represented Data. 19-26
  
• Suhail Ansari, Ron Kohavi, Llew Mason, Zijian Zheng:
  Integrating E-Commerce and Data Mining: Architecture and Challenges. 27-34
  
• Wai-Ho Au, Keith C. C. Chan:
  Classification with Degree of Membership: A Fuzzy Approach. 35-42
  
• José L. Balcázar, Yang Dai, Osamu Watanabe:
  Provably Fast Training Algorithms for Support Vector Machines. 43-50
  
• Krishna Bharat, Bay-Wei Chang, Monika Rauch Henzinger, Matthias Ruhl:
  Who Links to Whom: Mining Linkage between Web Sites. 51-58
  
• Catherine Blake, Wanda Pratt:
  Better Rules, Few Features: A Semantic Approach to Selecting Features from Text. 59-66
  
• Richard J. Bolton, David J. Hand:
  Significance Tests for Patterns in Continuous Data. 67-74
  
• Rong Chen, Krishnamoorthy Sivakumar, Hillol Kargupta:
  Distributed Web Mining Using Bayesian Networks from Multiple Data Streams. 75-82
  
• Jong-Sheng Cherng, Mei-Jung Lo:
  A Hypergraph Based Clustering Algorithm for Spatial Data Sets. 83-90
  
• David Maxwell Chickering, Christopher Meek, Robert Rounthwaite:
  Efficient Determination of Dynamic Split Points in a Decision Tree. 91-98
  
• Manoranjan Dash, Kian-Lee Tan, Huan Liu:
  Efficient Yet Accurate Clustering. 99-106
  
• Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Ming Gu, Horst D. Simon:
  A Min-max Cut Algorithm for Graph Partitioning and Data Clustering. 107-114
  
• Tapio Elomaa, Juho Rousu:
  Preprocessing Opportunities in Optimal Numerical Range Partitioning. 115-122
  
• Wei Fan, Matthew Miller, Salvatore J. Stolfo, Wenke Lee, Philip K. Chan:
  Using Artificial Anomalies to Detect Unknown and Known Network Intrusions. 123-130
  
• Tom Fawcett:
  Using Rule Sets to Maximize ROC Performance. 131-138
  
• Hichem Frigui, Mohamed Ben Hadj Rhouma:
  A Synchronization Based Algorithm for Discovering Ellipsoidal Clusters in Large Datasets. 139-146
  
• Joao Gama:
  Functional Trees for Classification. 147-154
  
• Floris Geerts, Bart Goethals, Jan Van den Bussche:
  A Tight Upper Bound on the Number of Candidate Patterns. 155-162
  
• Karam Gouda, Mohammed Javeed Zaki:
  Efficiently Mining Maximal Frequent Itemsets. 163-170
  
• Henner Graubitz, Myra Spiliopoulou, Karsten Winkler:
  The DIAsDEM Framework for Converting Domain-Specific Texts into XML Documents with Data Mining Techniques. 171-178
  
• Valerie Guralnik, George Karypis:
  A Scalable Algorithm for Clustering Sequential Data. 179-186
  
• Maria Halkidi, Michalis Vazirgiannis:
  Clustering Validity Assessment: Finding the Optimal Partitioning of a Data Set. 187-194
  
• Xiaofeng He, Chris H. Q. Ding, Hongyuan Zha, Horst D. Simon:
  Automatic Topic Identification Using Webpage Clustering. 195-202
  
• Johan Himberg, Kalle Korpiaho, Heikki Mannila, Johanna Tikanmäki, Hannu Toivonen:
  Time Series Segmentation for Context Recognition in Mobile Devices. 203-210
  
• Shoji Hirano, Shusaku Tsumoto:
  Indiscernibility Degree of Objects for Evaluating Simplicity of Knowledge in the Clustering Procedure. 211-217
  
• Tzung-Pei Hong, Yeong-Chyi Lee:
  Mining Coverage-Based Fuzzy Rules by Evolutional Computation. 218-224
  
• Ming-Chuan Hung, Don-Lin Yang:
  An Efficient Fuzzy C-Means Clustering Algorithm. 225-232
  
• Xiaohua Hu:
  Using Rough Sets Theory and Database Operations to Construct a Good Ensemble of Classifiers for Data Mining Applications. 233-240
  
• Hisao Ishibuchi, Takashi Yamamoto, Tomoharu Nakashima:
  Fuzzy Data Mining: Effect of Fuzzy Discretization. 241-248
  
• Chris Jermaine:
  The Computational Complexity of High-Dimensional Correlation Search. 249-256
  
• Mahesh V. Joshi, Vipin Kumar, Ramesh C. Agarwal:
  Evaluating Boosting Algorithms to Classify Rare Classes: Comparison and Improvements. 257-264
  
• Sung Young Jung, Taek-Soo Kim:
  An Agglomerative Hierarchical Clustering Using Partial Maximum Array and Incremental Similarity Computation Method. 265-272
  
• Konstantinos Kalpakis, Dhiral Gada, Vasundhara Puttagunta:
  Distance Measures for Effective Clustering of ARIMA Time-Series. 273-280
  
• Hillol Kargupta, Byung-Hoon Park:
  Mining Decision Trees from Data Streams in a Mobile Environment. 281-288
  
• Eamonn J. Keogh, Selina Chu, David Hart, Michael J. Pazzani:
  An Online Algorithm for Segmenting Time Series. 289-296
  
• Thomas Knight, Jon Timmis:
  AINE: An Immunological Approach to Data Mining. 297-304
  
• Marzena Kryszkiewicz:
  Concise Representation of Frequent Patterns Based on Disjunction-Free Generators. 305-312
  
• Michihiro Kuramochi, George Karypis:
  Frequent Subgraph Discovery. 313-320
  
• Henry E. Kyburg Jr.:
  Statistical Considerations in Learning from Data. 321-328
  
• Zarrin Langari, Frank Wm. Tompa:
  Subject Classification in the Oxford English Dictionary. 329-336
  
• Chang-Hung Lee, Cheng-Ru Lin, Ming-Syan Chen:
  On Mining General Temporal Association Rules in a Publication Database. 337-344
  
• Jung-Won Lee, Kiho Lee, Won Kim:
  Preparations for Semantics-Based XML Mining. 345-352
  
• Beitao Li, Wei-Cheng Lai, Edward Y. Chang, Kwang-Ting Cheng:
  Mining Image Features for Efficient Query Processing. 353-360
  
• Jiuyong Li, Hong Shen, Rodney W. Topor:
  Mining the Smallest Association Rule Set for Predictions. 361-368
  
• Wenmin Li, Jiawei Han, Jian Pei:
  CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules. 369-376
  
• Bing Liu, Yiming Ma, Ronnie Lee:
  Analyzing the Interestingness of Association Rules from the Temporal Dimension. 377-384
  
• Gary Livingston, John M. Rosenberg, Bruce G. Buchanan:
  Closing the Loop: An Agenda- and Justification-Based Framework for Selecting the Next Discovery Task to Perform. 385-392
  
• Gary Livingston, John M. Rosenberg, Bruce G. Buchanan:
  Closing the Loop: Heuristics for Autonomous Discovery. 393-400
  
• Wen-Hsiang Lu, Lee-Feng Chien, Hsi-Jian Lee:
  Anchor Text Mining for Translation of Web Queries. 401-408
  
• Sheng Ma, Joseph L. Hellerstein:
  Mining Mutually Dependent Patterns. 409-416
  
• Paul Munteanu, Mohamed Bendou:
  The EQ Framework for Learning Equivalence Classes of Bayesian Networks. 417-424
  
• Steven Noel, Vijay V. Raghavan, Chee-Hung Henry Chu:
  Visualizing Association Mining Results through Hierarchical Clusters. 425-432
  
• Carlos Ordonez, Edward Omiecinski, Levien de Braal, Cesar A. Santana, Norberto F. Ezquerra, José A. Taboada, C. David Cooke, Elizabeth Krawczynska, Ernest V. Garcia:
  Mining Constrained Association Rules to Predict Heart Disease. 433-440
  
• Jian Pei, Jiawei Han, Hongjun Lu, Shojiro Nishio, Shiwei Tang, Dongqing Yang:
  H-Mine: Hyper-Structure Mining of Frequent Patterns in Large Databases. 441-448
  
• Chang-Shing Perng, Haixun Wang, Sheng Ma, Joseph L. Hellerstein:
  FARM: A Framework for Exploring Mining Spaces with Multiple Attributes. 449-456
  
• Kimmo Raivio, Olli Simula, Jaana Laiho:
  Neural Analysis of Mobile Radio Access Network. 457-466
  
• Graeme Richards, Victor J. Rayward-Smith:
  Discovery of Association Rules in Tabular Data. 465-472
  
• Lior Rokach, Oded Maimon:
  Theory and Applications of Attribute Decomposition. 473-480
  
• Pierre-Yves Rolland:
  FlExPat: Flexible Extraction of Sequential Patterns. 481-488
  
• Sigal Sahar:
  Interestingness PreProcessing. 489-496
  
• Ying Sai, Yiyu Yao, Ning Zhong:
  Data Analysis and Mining in Ordered Information Tables. 497-504
  
• Masakazu Seno, George Karypis:
  LPMiner: An Algorithm for Finding Frequent Itemsets Using Length-Decreasing Support Constraint. 505-512
  
• Joaquim Ferreira da Silva, João Mexia, Carlos Agra Coelho, José Gabriel Pereira Lopes:
  Document Clustering and Cluster Topic Extraction in Multilingual Corpora. 513-520
  
• Aixin Sun, Ee-Peng Lim:
  Hierarchical Text Classification and Evaluation. 521-528
  
• François Velin, Pascale Kuntz, Henri Briand:
  Web Cartography for Online State Promotion: An Algorithm for Clustering Web Resources. 529-535
  
• Ching-Yao Wang, Tzung-Pei Hong, Shian-Shyong Tseng:
  Maintenance of Sequential Patterns for Record Deletion. 536-541
  
• Haixun Wang, Philip S. Yu:
  SSDT: A Scalable Subspace-Splitting Classifier for Biased Data. 542-549
  
• Wei Wang, Jiong Yang, Philip S. Yu:
  Meta-patterns: Revealing Hidden Periodic Patterns. 550-557
  
• Virginia Wheway:
  Using Boosting to Simplify Classification Models. 558-565
  
• Ning Zhong, Y. Y. Yao, Muneaki Ohshima, Setsuo Ohsuga:
  Interestingness, Peculiarity, and Multi-Database Mining. 566-576
  

Posters

• Fernando Alonso, Juan Pedro Caraça-Valente, Loïc Martínez, César Montes:
  Discovering Similar Patterns for Characterising Time Series in a Medical Domain. 577-579
  
• Nitesh V. Chawla, Steven Eschrich, Lawrence O. Hall:
  Creating Ensembles of Classifiers. 580-581
  
• Jie Chen, Haiying Li, Shiwei Tang:
  Association Rules Enhanced Classification of Underwater Acoustic Signal. 582-583
  
• June-Suh Cho, Nabil R. Adam:
  Efficient Splitting Rules Based on the Probabilities of Pre-assigned Intervals. 584-585
  
• Honghua Dai, Xiaoshu Hang, Gang Li:
  Inexact Field Learning: An Approach to Induce High Quality Rules from Low Quality Data. 586-588
  
• Carlotta Domeniconi, Dimitrios Gunopulos:
  Incremental Support Vector Machine Construction. 589-592
  
• Wolfgang Gaul, Lars Schmidt-Thieme:
  Mining Generalized Association Rules for Sequential and Path Data. 593-596
  
• Rayid Ghani:
  Combining Labeled and Unlabeled Data for Text Classification with a Large Number of Categories. 597-598
  
• Daniel Gillblad, Anders Holst:
  Dependency Derivation in Industrial Process Data. 599-602
  
• Sherri K. Harms, Jitender S. Deogun, Jamil Saquer, Tsegaye Tadesse:
  Discovering Representative Episodal Association Rules from Event Sequences Using Frequent Closed Episode Sets and Event Constraints. 603-606
  
• Andreas Hotho, Alexander Maedche, Steffen Staab:
  Text Clustering Based on Good Aggregations. 607-608
  
• Hasan M. Jamil:
  Ad Hoc Association Rule Mining as SQL3 Queries. 609-612
  
• Viviane Crestana-Jensen, Nandit Soparkar:
  Heuristic Optimization for Decentralized Frequent Itemset Counting. 613-614
  
• Gang Li, Fu Tong, Honghua Dai:
  Evolutionary Structure Learning Algorithm for Bayesian Network and Penalized Mutual Information Metric. 615-616
  
• Xu Liang, Yao Liang:
  Applications of Data Mining in Hydrology. 617-620
  
• Zhiyong Liu, Lei Xu:
  RPCL-Based Local PCA Algorithm. 621-622
  
• Manolis Maragoudakis, Katia Kermanidis, Nikos Fakotakis, George K. Kokkinakis:
  Learning Automatic Acquisition of Subcategorization Frames Using Bayesian Inference and Support Vector Machines. 623-625
  
• Petri Myllymäki, Tomi Silander, Henry Tirri, Pekka Uronen:
  Bayesian Data Mining on the Web with B-Course. 626-629
  
• Tadashi Nomoto, Yuji Matsumoto:
  An Experimental Comparison of Supervised and Unsupervised Approaches to Text Summarization. 630-632
  
• Carlos Ordonez, Edward Omiecinski, Norberto F. Ezquerra:
  A Fast Algorithm to Cluster High Dimensional Basket Data. 633-636
  
• Jürgen Paetz:
  Metric Rule Generation with Septic Shock Patient Data. 637-638
  
• Viet Phan Luong:
  The Representative Basis for Association Rules. 639-640
  
• Stefan Rüping:
  Incremental Learning with Support Vector Machines. 641-642
  
• Guillermo Sánchez-Díaz, José Ruiz-Shulcloper:
  A Clustering Method for Very Large Mixed Data Sets. 643-644
  
• Tobias Scheffer, Christian Decomain, Stefan Wrobel:
  Mining the Web with Active Hidden Markov Models. 645-646
  
• Pascal Soucy, Guy W. Mineau:
  A Simple KNN Algorithm for Text Categorization. 647-648
  
• Sam Steingold, Richard Wherry, Gregory Piatetsky-Shapiro:
  Measuring Real-Time Predictive Models. 649-650
  
• Fengzhan Tian, Hongwei Zhang, Yuchang Lu, Chunyi Shi:
  Incremental Learning of Bayesian Networks with Hidden Variables. 651-652
  
• Fan-Chen Tseng, Ching-Chi Hsu, Henry Chen:
  Mining Frequent Closed Itemsets with the Frequent Pattern List. 653-654
  
• Hui Wang, Ivo Düntsch, David A. Bell, Dayou Liu:
  Classification through Maximizing Density. 655-656
  
• Lei Wang, Licheng Jiao:
  An Immune Neural Network Used for Classification. 657-658
  
• Xiong Wang:
  alpha-Surface and Its Application to Mining Protein Data. 659-662
• Show-Jane Yen, Yue-Shi Lee:
  An Efficient Data Mining Technique for Discovering Interesting Sequential Patterns. 663-664
  
• Osmar R. Zaïane, Mohammad El-Hajj, Paul Lu:
  Fast Parallel Association Rule Mining without Candidacy Generation. 665-668
  
• Bernard Zenko, Ljupco Todorovski, Saso Dzeroski:
  A Comparison of Stacking with Meta Decision Trees to Bagging, Boosting, and Stacking with other Methods. 669-670
  
• Du Zhang, Quoc Luan Ha, Meiliu Lu:
  Mining California Vital Statistics Data. 671-672
  
• Qinghua Zou, Wesley W. Chu, David B. Johnson, Henry Chiu:
  A Pattern Decomposition (PD) Algorithm for Finding All Frequent Patterns in Large Datasets. 673-674
  

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