ICDM - Main-Track Regular Papers Empirical Comparison of Various Reinforcement Learning Strategies for Sequential Targeted Marketing Naoki Abe Edwin P. D. Pednault Haixun Wang Bianca Zadrozny Wei Fan Chidanand Apté Investigative Profiling with Computer Forensic Log Data and Association Rules Tamas Abraham Olivier Y. de Vel Text Document Categorization by Term Association Maria-Luiza Antonie Osmar R. Zaïane Online Algorithms for Mining Semi-structured Data Stream Tatsuya Asai Hiroki Arimura Kenji Abe Shinji Kawasoe Setsuo Arikawa A Lazy Approach to Pruning Classification Rules Elena Baralis Paolo Garza High Performance Data Mining Using the Nearest Neighbor Join Christian Böhm Florian Krebs Mining Molecular Fragments: Finding Relevant Substructures of Molecules Christian Borgelt Michael R. Berthold Mining General Temporal Association Rules for Items with Different Exhibition Periods Cheng-Yue Chang Ming-Syan Chen Chang-Hung Lee Learning with Progressive Transductive Support Vector Machine Yisong Chen Guoping Wang Shihai Dong Towards Automatic Generation of Query Taxonomy: A Hierarchical Query Clustering Approach Shui-Lung Chuang Lee-Feng Chien Evolutionary Time Series Segmentation for Stock Data Mining Fu-Lai Chung Tak-chung Fu Robert W. P. Luk Vincent Ng Using functional PCA for cardiac motion exploration Denis Clot Unsupervised Segmentation of Categorical Time Series into Episodes Paul R. Cohen Brent Heeringa Niall M. Adams Speed-up Iterative Frequent Itemset Mining with Constraint Changes Gao Cong Bing Liu Feature Selection for Clustering - A Filter Solution Manoranjan Dash Kiseok Choi Peter Scheuermann Huan Liu A Theory of Inductive Query Answering Luc De Raedt Manfred Jaeger Sau Dan Lee Heikki Mannila Iterative Clustering of High Dimensional Text Data Augmented by Local Search Inderjit S. Dhillon Yuqiang Guan J. Kogan Cluster merging and splitting in hierarchical clustering algorithms Chris H. Q. Ding Xiaofeng He Adaptive dimension reduction for clustering high dimensional data Chris H. Q. Ding Xiaofeng He Hongyuan Zha Horst D. Simon Modal-style operators in qualitative data analysis Ivo Düntsch Günther Gediga Progressive Modeling Wei Fan Haixun Wang Philip S. Yu Shaw-hwa Lo Salvatore J. Stolfo Unsupervised Clustering of Symbol Strings and Context Recognition John A. Flanagan Jani Mäntyjärvi Johan Himberg A Parameterless Method for Efficiently Discovering Clusters of Arbitrary Shape in Large Datasets Andrew Foss Osmar R. Zaïane Discriminative Category Matching: Efficient Text Classification for Huge Document Collections Gabriel Pui Cheong Fung Jeffrey Xu Yu Hongjun Lu Using Text Mining to Infer Semantic Attributes for Retail Data Mining Rayid Ghani Andrew E. Fano Phrase-based Document Similarity Based on an Index Graph Model Khaled M. Hammouda Mohamed S. Kamel Mining Top-K Frequent Closed Patterns without Minimum Support Jiawei Han Jianyong Wang Ying Lu Petre Tzvetkov Mining Similar Temporal Patterns in Long Time-Series Data and Its Application to Medicine Shoji Hirano Shusaku Tsumoto Mining Generalized Association Rules Using Pruning Techniques Yin-Fu Huang Chiech-Ming Wu A Formal Model for User Preference Sung Young Jung Jeong-Hee Hong Taek-Soo Kim Convex Hull Ensemble Machine Yongdai Kim Recognition of Common Areas in a Web Page Using Visual Information: a possible application in a page classification Milos Kovacevic Michelangelo Diligenti Marco Gori Veljko M. Milutinovic Discovering Frequent Geometric Subgraphs Michihiro Kuramochi George Karypis Adapting classification rule induction to subgroup discovery Nada Lavrac Peter A. Flach Branko Kavsek Ljupco Todorovski Linear Causal Model Discovery Using the MML criterion Gang Li Honghua Dai Yiqing Tu Attribute (Feature) Completion - The Theory of Attributes from Data Mining Prospect Tsay Young Lin O-Cluster: Scalable Clustering of Large High Dimensional Data Sets Boriana L. Milenova Marcos M. Campos Employing Discrete Bayes Error rate for discretization and feature selection Ankush Mittal Loong Fah Cheong Feature Selection Algorithms: A Survey and Experimental Evaluation Luis Carlos Molina Lluís Belanche Àngela Nebot Multivariate supervised discretization, a neighborhood graph approach Fabrice Muhlenbach Ricco Rakotomalala Mining Association Rules from Stars Eric Ka Ka Ng Ada Wai-Chee Fu Ke Wang PERUSE: An Unsupervised Algorithm for Finding Recurrig Patterns in Time Series Tim Oates Adaptive and Resource-Aware Mining of Frequent Sets Salvatore Orlando Paolo Palmerini Raffaele Perego Fabrizio Silvestri A new implementation technique for fast Spectral based document retrieval systems Laurence A. F. Park Marimuthu Palaniswami Kotagiri Ramamohanarao Efficient Progressive Sampling for Association Rules Srinivasan Parthasarathy Efficient Discovery of Common Substructures in Macromolecules Srinivasan Parthasarathy Matt Coatney Mining Motifs in Massive Time Series Databases Pranav Patel Eamonn J. Keogh Jessica Lin Stefano Lonardi On Computing Condensed Frequent Pattern Bases. Jian Pei Guozhu Dong Wei Zou Jiawei Han Automatic Web Page Classification in a Dynamic and Hierarchical Way Xiaogang Peng Ben Choi User-directed Exploration of Mining Space with Multiple Attributes Chang-Shing Perng Haixun Wang Sheng Ma Joseph L. Hellerstein Mining Significant Associations in Large Scale Text Corpora Prabhakar Raghavan Panayiotis Tsaparas On a Capacity Control Using Boolean Kernels for the Learning of Boolean Functions Ken Sadohara SLPMiner: An Algorithm for Finding Frequent Sequential Patterns Using Length-Decreasing Support Constraint Masakazu Seno George Karypis Objective-Oriented Utility-Based Association Mining Yi-Dong Shen Zhong Zhang Qiang Yang A Self-Organizing Map with Expanding Force for Data Clustering and Visualization Wing-Ho Shum Huidong Jin Kwong-Sak Leung Man Leung Wong On the Mining of Substitution Rules for Statistically Dependent Items Wei-Guang Teng Ming-Jyh Hsieh Ming-Syan Chen TreeFinder: a First Step towards XML Data Mining Alexandre Termier Marie-Christine Rousset Michèle Sebag Computing Frequent Graph Patterns from Semistructured Data N. Vanetik Ehud Gudes Solomon Eyal Shimony Estimating the number of segments in time series data using permutation tests Kari Vasko Hannu Toivonen Predicting Rare Events In Temporal Domains Ricardo Vilalta Sheng Ma Mining Associations by Pattern Structure in Large Relational Tables Haixun Wang Chang-Shing Perng Sheng Ma Philip S. Yu Comparison of Lazy Bayesian Rule and Tree-Augmented Bayesian Learning. Zhihai Wang Geoffrey I. Webb A Hybrid Approach to Discover Bayesian Networks From Databases Using Evolutionary Programming Man Leung Wong Shing Yan Lee Kwong-Sak Leung Adapting Information Extraction Knowledge For Unseen Web Sites Tak-Lam Wong Wai Lam From Path Tree To Frequent Patterns: A Framework for Mining Frequent Patterns Yabo Xu Jeffrey Xu Yu Guimei Liu Hongjun Lu Mining Case Bases for Action Recommendation Qiang Yang Hong Cheng Adaptive Ripple Down Rules Method based on Minimum Description Length Principle Tetsuya Yoshida Hiroshi Motoda Takashi Washio Heterogeneous Learner for Web Page Classification Hwanjo Yu Kevin Chen-Chuan Chang Jiawei Han Using Category-Based Adherence to Cluster Market-Basket Data Ching-Huang Yun Kun-Ta Chuang Ming-Syan Chen A Comparison Study on Algorithms for Incremental Update of Frequent Sequences Minghua Zhang Ben Kao Chi Lap Yip On Active Learning for Data Acquisition Zhiqiang Zheng Balaji Padmanabhan SmartMiner: A Depth First Algorithm Guided by Tail Information for Mining Maximal Frequent Itemsets Qinghua Zou Wesley W. Chu Baojing Lu Return to ICDM session listing DiSC'03 © 2003 Association for Computing Machinery