The papers on rough set theory and its applications placed in this volume present a wide spectrum of problems representative to the present. Therefore many concepts dwelled on in rough set theory are not entirely new, nevertheless the theory can be viewed as an independent discipline on its own rights.

1. Introducing the Book.- 1. Applications.- 2. Rough Approximation of a Preference Relation in a Pairwise Comparison Table.- 3. Learning Decision Rules from Similarity Based Rough Approximations.- 4. Discovery of Data Patterns with Applications to Decomposition and Classification Problems.- 5. Answering Non-Standard Queries in Distributed Knowledge-Based Systems.- 6. Approximation Spaces, Reducts and Representatives.- 7. Data Mining: A Probabilistic Rough Set Approach.- 2: Case Studies.- 8. Soft Processing of Audio Signals.- 9. A Rough Set Approach to Information Retrieval.- 10. Extraction Method Based on Rough Set Theory of Rule-Type Knowledge from Diagnostic Cases of Slope-Failure Danger Levels.- 11. Soft Computing-Based Recognition of Musical Sounds.- 12. Rough Sets in Industrial Applications.- 13. Rough Sets in Economic Applications.- 14. Multistage Rough Set Analysis of Therapeutic Experience with Acute Pancreatitis.- 15. Reduction Methods for Medical Data.- 16. Formalization and Induction of Medical Expert System Rules Based on Rough Set Theory.- 17. Rough Sets for Database Marketing.- 18. A New Halftoning Method Based on Error Diffusion with Rough Set Filtering.- 3: Hybrid Approaches.- 19. IRIS Revisited: A Comparison of Discriminant and Enhanced Rough Set Data Analysis.- 20. Applications of Rough Patterns.- 21. Time and Clock Information Systems: Concepts and Roughly Fuzzy Petri Net Models.- 22. The Synthesis Problem of Concurrent Systems Specified by Dynamic Information Systems.- 23. Rough Sets and Artificial Neural Networks.- 24. Genetic Algorithms in Decomposition and Classification Problems.- Appendix 1: Rough Set Bibliography.- Selected Bibliography on Rough Sets.- Appendix 2: Software Systems.- GROBIAN.- RSDM: Rough sets Data Miner, A System to Add Data Mining Capabilities to RDBMS.- LERS — A Knowledge Discovery System.- TRANCE: A Tool for Rough Data Analysis, Classification, and Clustering.- ProbRough — A System for Probabilistic Rough Classifiers Generation.- The ROSETTA Software System.- RSL — The Rough Set Library.- Rough Family — Software Implementation of the Rough Set Theory.- TAS: Tools for Analysis and Synthesis of Concurrent Processes Using Rough Set Methods.- RoughFuzzyLab — A System for Data Mining and Rough and Fuzzy Sets Based Classification.- PRIMEROSE.- KDD-R: Rough Sets-Based Data Mining System.