Advances in Knowledge Discovery and Data Mining

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.