Compact Representations of Sequential Classification Rules -- An Algorithm for Mining Weighted Dense Maximal 1-Complete Regions -- Mining Linguistic Trends from Time Series -- Latent Semantic Space for Web Clustering -- A Logical Framework for Template Creation and Information Extraction -- A Bipolar Interpretation of Fuzzy Decision Trees -- A Probability Theory Perspective on the Zadeh Fuzzy System -- Three Approaches to Missing Attribute Values: A Rough Set Perspective -- MLEM2 Rule Induction Algorithms: With and Without Merging Intervals -- Towards a Methodology for Data Mining Project Development: The Importance of Abstraction -- Fining Active Membership Functions in Fuzzy Data Mining -- A Compressed Vertical Binary Algorithm for Mining Frequent Patterns -- Naïve Rules Do Not Consider Underlying Causality -- Inexact Multiple-Grained Causal Complexes -- Does Relevance Matter to Data Mining Research? -- E-Action Rules -- Mining E-Action Rules, System DEAR -- Definability of Association Rules and Tables of Critical Frequencies -- Classes of Association Rules: An Overview -- Knowledge Extraction from Microarray Datasets Using Combined Multiple Models to Predict Leukemia Types -- On the Complexity of the Privacy Problem in Databases -- Ensembles of Least Squares Classifiers with Randomized Kernels -- On Pseudo-Statistical Independence in a Contingency Table -- Role of Sample Size and Determinants in Granularity of Contingency Matrix -- Generating Concept Hierarchies from User Queries -- Mining Efficiently Significant Classification Association Rules -- Data Preprocessing and Data Mining as Generalization -- Capturing Concepts and Detecting Concept-Drift from Potential Unbounded, Ever-Evolving and High-Dimensional Data Streams -- A Conceptual Framework of Data Mining -- How to Prevent Private Data from being Disclosed to a Malicious Attacker -- Privacy-Preserving Naive Bayesian Classification over Horizontally Partitioned Data -- Using Association Rules for Classification from Databases Having Class Label Ambiguities: A Belief Theoretic Method.