Rough Set Methods and Applications New Developments in Knowledge Discovery in Information Systems /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Polkowski, Lech (Editor, http://id.loc.gov/vocabulary/relators/edt), Tsumoto, Shusaku (Editor, http://id.loc.gov/vocabulary/relators/edt), Lin, Tsau Y. (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Heidelberg : Physica-Verlag HD : Imprint: Physica, 2000.
• Edition: 1st ed. 2000.
• Series: Studies in Fuzziness and Soft Computing, 56
• Subjects: Artificial intelligence.; Mathematical logic.; Information technology.; Business-Data processing.; Artificial Intelligence.; Mathematical Logic and Formal Languages.; IT in Business.

Rough set approach to reasoning under uncertainty is based on inducing knowledge representation from data under constraints expressed by discernibility or, more generally, similarity of objects. Knowledge derived by this approach consists of reducts, decision or association rules, dependencies, temp...

Table of Contents:

• 1. Introduction
• Introducing the Book
• 1. A Rough Set Perspective on Knowledge Discovery in Information Systems: An Essay on the Topic of the Book
• 2. Methods and Applications: Reducts, Similarity, Mereology
• 2. Rough Set Algorithms in Classification Problem
• 3. Rough Mereology in Information Systems. A Case Study: Qualitative Spatial Reasoning
• 4. Knowledge Discovery by Application of Rough Set Models
• 5. Various Approaches to Reasoning with Frequency Based Decision Reducts: A Survey
• 3. Methods and Applications: Regular Pattern Extraction, Concurrency
• 6. Regularity Analysis and its Applications in Data Mining
• 7. Rough Set Methods for the Synthesis and Analysis of Concurrent Processes
• 4. Methods and Applications: Algebraic and Statistical Aspects, Conflicts, Incompleteness
• 8. Conflict Analysis
• 9. Logical and Algebraic Techniques for Rough Set Data Analysis
• 10. Statistical Techniques for Rough Set Data Analysis
• 11. Data Mining in Incomplete Information Systems from Rough Set Perspective
• 5. Afterword
• 12. Rough Sets and Rough Logic: A KDD Perspective
• Appendix: Selected Bibliofgraphy on Rough Sets.