Successes and New Directions in Data Mining

Successes and New Directions in Data Mining

Preface

Chapter I

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Why Fuzzy Set Theory is Useful in Data Mining

Chapter II

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SeqPAM—A Sequence Clustering Algorithm for Web Personalization

Chapter III

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Using Mined Patterns for XML Query Answering

Chapter IV

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On the Usage of Structural Information in Constrained Semi-Supervised Clustering of XML Documents

Chapter V

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Modeling and Managing Heterogeneous Patterns—The PSYCHO Experience

Chapter VI

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Deterministic Motif Mining in Protein Databases

Chapter VII

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Data Mining and Knowledge Discovery in Metabolomics

Chapter VIII

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Handling Local Patterns in Collaborative Structuring

Chapter IX

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Pattern Mining and Clustering on Image Databases

Chapter X

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Semantic Integration and Knowledge Discovery for Environmental Research

Chapter XI

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Visualizing Multi Dimensional Data

Chapter XII

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Privacy Preserving Data Mining, Concepts, Techniques, and Evaluation Methodologies

Chapter XIII

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Mining Data-Streams

Compilation of References