Keynote Presentations -- Incompleteness in Data Mining -- Mining E-Commerce Data: The Good, the Bad, and the Ugly -- Seamless Integration of Data Mining with DBMS and Applications -- Web Mining -- Applying Pattern Mining to Web Information Extraction -- Empirical Study of Recommender Systems Using Linear Classifiers -- iJADE eMiner - A Web-Based Mining Agent Based on Intelligent Java Agent Development Environment (iJADE) on Internet Shopping -- A Characterized Rating Recommend System -- Discovery of Frequent Tree Structured Patterns in Semistructured Web Documents -- Text Mining -- Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification -- Predictive Self-Organizing Networks for Text Categorization -- Meta-learning Models for Automatic Textual Document Categorization -- Efficient Algorithms for Concept Space Construction -- Topic Detection, Tracking, and Trend Analysis Using Self-Organizing Neural Networks -- Automatic Hypertext Construction through a Text Mining Approach by Self-Organizing Maps -- Applications and Tools -- Semantic Expectation-Based Causation Knowledge Extraction: A Study on Hong Kong Stock Movement Analysis -- A Toolbox Approach to Flexible and Efficient Data Mining -- Determining Progression in Glaucoma Using Visual Fields -- Seabreeze Prediction Using Bayesian Networks -- Semi-supervised Learning in Medical Image Database -- On Application of Rough Data Mining Methods to Automatic Construction of Student Models -- Concept Hierarchies -- Concept Approximation in Concept Lattice -- Generating Concept Hierarchies/Networks: Mining Additional Semantics in Relational Data -- Representing Large Concept Hierarchies Using Lattice Data Structure -- Feature Selection -- Feature Selection for Temporal Health Records -- Boosting the Performance of Nearest Neighbour Methods with Feature Selection -- Feature Selection for Meta-learning -- Interestingness -- Efficient Mining of Niches and Set Routines -- Evaluation of Interestingness Measures for Ranking Discovered Knowledge -- Peculiarity Oriented Mining and Its Application for Knowledge Discovery in Amino-Acid Data -- Sequence Mining -- Mining Sequence Patterns from Wind Tunnel Experimental Data for Flight Control -- Scalable Hierarchical Clustering Method for Sequences of Categorical Values -- FFS - An I/O-Efficient Algorithm for Mining Frequent Sequences -- Sequential Index Structure for Content-Based Retrieval -- Spatial and Temporal Mining -- The S 2-Tree: An Index Structure for Subsequence Matching of Spatial Objects -- Temporal Data Mining Using Hidden Markov-Local Polynomial Models -- Patterns Discovery Based on Time-Series Decomposition -- Criteria on Proximity Graphs for Boundary Extraction and Spatial Clustering -- Micro Similarity Queries in Time Series Database -- Association Mining -- Mining Optimal Class Association Rule Set -- Generating Frequent Patterns with the Frequent Pattern List -- User-Defined Association Mining -- Direct and Incremental Computing of Maximal Covering Rules -- Towards Efficient Data Re-mining (DRM) -- Data Allocation Algorithm for Parallel Association Rule Discovery -- Classification and Rule Induction -- Direct Domain Knowledge Inclusion in the PA3 Rule Induction Algorithm -- Hierarchical Classification of Documents with Error Control -- An Efficient Data Compression Approach to the Classification Task -- Combining the Strength of Pattern Frequency and Distance for Classification -- A Scalable Algorithm for Rule Post-pruning of Large Decision Trees -- Optimizing the Induction of Alternating Decision Trees -- Building Behaviour Knowledge Space to Make Classification Decision -- Clustering -- Efficient Hierarchical Clustering Algorithms Using Partially Overlapping Partitions -- A Rough Set-Based Clustering Method with Modification of Equivalence Relations -- Importance of Individual Variables in the k-Means Algorithm -- A Hybrid Approach to Clustering in Very Large Databases -- Advanced Topics and New Methods -- A Similarity Indexing Method for the Data Warehousing - Bit-Wise Indexing Method -- Rule Reduction over Numerical Attributes in Decision Trees Using Multilayer Perceptron -- Knowledge Acquisition from Both Human Expert and Data -- Neighborhood Dependencies for Prediction -- Learning Bayesian Networks with Hidden Variables Using the Combination of EM and Evolutionary Algorithms -- Interactive Construction of Decision Trees -- An Improved Learning Algorithm for Augmented Naive Bayes -- Generalised RBF Networks Trained Using an IBL Algorithm for Mining Symbolic Data.