Principles of Data Mining and Knowledge Discovery

Regular Papers.- Self-Similar Layered Hidden Markov Models.- Automatic Text Summarization Using Unsupervised and Semi-supervised Learning.- Detecting Temporal Change in Event Sequences: An Application to Demographic Data.- Knowledge Discovery in Multi-label Phenotype Data.- Computing Association Rules Using Partial Totals.- Gaphyl: A Genetic Algorithms Approach to Cladistics.- Parametric Approximation Algorithms for High-Dimensional Euclidean Similarity.- Data Structures for Minimization of Total Within-Group Distance for Spatio-temporal Clustering.- Non-crisp Clustering by Fast, Convergent, and Robust Algorithms.- Pattern Extraction for Time Series Classification.- Specifying Mining Algorithms with Iterative User-Defined Aggregates: A Case Study.- Interesting Fuzzy Association Rules in Quantitative Databases.- Interestingness Measures for Fuzzy Association Rules.- A Data Set Oriented Approach for Clustering Algorithm Selection.- Fusion of Meta-knowledge and Meta-data for Case-Based Model Selection.- Discovery of Temporal Patterns.- Temporal Rule Discovery for Time-Series Satellite Images and Integration with RDB.- Using Grammatical Inference to Automate Information Extraction from the Web.- Biological Sequence Data Mining.- Implication-Based Fuzzy Association Rules.- A General Measure of Rule Interestingness.- Error Correcting Codes with Optimized Kullback-Leibler Distances for Text Categorization.- Propositionalisation and Aggregates.- Algorithms for the Construction of Concept Lattices and Their Diagram Graphs.- Data Reduction Using Multiple Models Integration.- Discovering Fuzzy Classification Rules with Genetic Programming and Co-evolution.- Sentence Filtering for Information Extraction in Genomics, a Classification Problem.- Text Categorization and Semantic Browsing with Self-Organizing Maps on Non-euclidean Spaces.- A Study on the Hierarchical Data Clustering Algorithm Based on Gravity Theory.- Internet Document Filtering Using Fourier Domain Scoring.-