Ebook: Rough Sets in Knowledge Discovery 2: Applications, Case Studies and Software Systems

The papers on rough set theory and its applications placed in this volume present a wide spectrum of problems representative to the present. stage of this theory. Researchers from many countries reveal their rec.ent results on various aspects of rough sets. The papers are not confined only to mathematical theory but also include algorithmic aspects, applications and information about software designed for data analysis based on this theory. The volume contains also list of selected publications on rough sets which can be very useful to every one engaged in research or applications in this domain and sometimes perhaps unaware of results of other authors. The book shows that rough set theory is a vivid and vigorous domain with serious results to its credit and bright perspective for future developments. It lays on the crossroads of fuzzy sets, theory of evidence, neural networks, Petri nets and many other branches of AI, logic and mathematics. These diverse connec­ tions seem to be a very fertile feature of rough set theory and have essentially contributed to its wide and rapid expansion. It is worth mentioning that its philosophical roots stretch down from Leibniz, Frege and Russell up to Popper. 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. Rough set theory has found many interesting real life applications in medicine, banking, industry and others.

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The ideas and techniques worked out in Rough Set Theory allow for knowledge reduction and to finding near - to - functional dependencies in data. This fact determines the importance of these techniques for the rapidly growing field of knowledge discovery. Volume 1 and 2 will bring together articles covering the present state of the methods developed in this field of research. Among the topics covered we may mention: rough mereology and rough mereological approach to knowledge discovery in distributed systems; discretization and quantization of attributes; morphological aspects of rough set theory; analysis of default rules in the framework of rough set theory.

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The ideas and techniques worked out in Rough Set Theory allow for knowledge reduction and to finding near - to - functional dependencies in data. This fact determines the importance of these techniques for the rapidly growing field of knowledge discovery. Volume 1 and 2 will bring together articles covering the present state of the methods developed in this field of research. Among the topics covered we may mention: rough mereology and rough mereological approach to knowledge discovery in distributed systems; discretization and quantization of attributes; morphological aspects of rough set theory; analysis of default rules in the framework of rough set theory.
Content:
Front Matter....Pages I-X
Introducing the Book....Pages 1-9
Front Matter....Pages 11-11
Rough Approximation of a Preference Relation in a Pairwise Comparison Table....Pages 13-36
Learning Decision Rules from Similarity Based Rough Approximations....Pages 37-54
Discovery of Data Patterns with Applications to Decomposition and Classification Problems....Pages 55-97
Answering Non-Standard Queries in Distributed Knowledge-Based Systems....Pages 98-108
Approximation Spaces, Reducts and Representatives....Pages 109-126
Data Mining: A Probabilistic Rough Set Approach....Pages 127-144
Front Matter....Pages 145-145
Soft Processing of Audio Signals....Pages 147-165
A Rough Set Approach to Information Retrieval....Pages 166-177
Extraction Method Based on Rough Set Theory of Rule-Type Knowledge from Diagnostic Cases of Slope-Failure Danger Levels....Pages 178-192
Soft Computing-Based Recognition of Musical Sounds....Pages 193-213
Rough Sets in Industrial Applications....Pages 214-237
Rough Sets in Economic Applications....Pages 238-271
Multistage Rough Set Analysis of Therapeutic Experience with Acute Pancreatitis....Pages 272-294
Reduction Methods for Medical Data....Pages 295-306
Formalization and Induction of Medical Expert System Rules Based on Rough Set Theory....Pages 307-323
Rough Sets for Database Marketing....Pages 324-335
A New Halftoning Method Based on Error Diffusion with Rough Set Filtering....Pages 336-342
Front Matter....Pages 343-343
IRIS Revisited: A Comparison of Discriminant and Enhanced Rough Set Data Analysis....Pages 345-368
Applications of Rough Patterns....Pages 369-384
Front Matter....Pages 343-343
Time and Clock Information Systems: Concepts and Roughly Fuzzy Petri Net Models....Pages 385-417
The Synthesis Problem of Concurrent Systems Specified by Dynamic Information Systems....Pages 418-448
Rough Sets and Artificial Neural Networks....Pages 449-470
Genetic Algorithms in Decomposition and Classification Problems....Pages 471-487
Back Matter....Pages 489-601

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The ideas and techniques worked out in Rough Set Theory allow for knowledge reduction and to finding near - to - functional dependencies in data. This fact determines the importance of these techniques for the rapidly growing field of knowledge discovery. Volume 1 and 2 will bring together articles covering the present state of the methods developed in this field of research. Among the topics covered we may mention: rough mereology and rough mereological approach to knowledge discovery in distributed systems; discretization and quantization of attributes; morphological aspects of rough set theory; analysis of default rules in the framework of rough set theory.
Content:
Front Matter....Pages I-X
Introducing the Book....Pages 1-9
Front Matter....Pages 11-11
Rough Approximation of a Preference Relation in a Pairwise Comparison Table....Pages 13-36
Learning Decision Rules from Similarity Based Rough Approximations....Pages 37-54
Discovery of Data Patterns with Applications to Decomposition and Classification Problems....Pages 55-97
Answering Non-Standard Queries in Distributed Knowledge-Based Systems....Pages 98-108
Approximation Spaces, Reducts and Representatives....Pages 109-126
Data Mining: A Probabilistic Rough Set Approach....Pages 127-144
Front Matter....Pages 145-145
Soft Processing of Audio Signals....Pages 147-165
A Rough Set Approach to Information Retrieval....Pages 166-177
Extraction Method Based on Rough Set Theory of Rule-Type Knowledge from Diagnostic Cases of Slope-Failure Danger Levels....Pages 178-192
Soft Computing-Based Recognition of Musical Sounds....Pages 193-213
Rough Sets in Industrial Applications....Pages 214-237
Rough Sets in Economic Applications....Pages 238-271
Multistage Rough Set Analysis of Therapeutic Experience with Acute Pancreatitis....Pages 272-294
Reduction Methods for Medical Data....Pages 295-306
Formalization and Induction of Medical Expert System Rules Based on Rough Set Theory....Pages 307-323
Rough Sets for Database Marketing....Pages 324-335
A New Halftoning Method Based on Error Diffusion with Rough Set Filtering....Pages 336-342
Front Matter....Pages 343-343
IRIS Revisited: A Comparison of Discriminant and Enhanced Rough Set Data Analysis....Pages 345-368
Applications of Rough Patterns....Pages 369-384
Front Matter....Pages 343-343
Time and Clock Information Systems: Concepts and Roughly Fuzzy Petri Net Models....Pages 385-417
The Synthesis Problem of Concurrent Systems Specified by Dynamic Information Systems....Pages 418-448
Rough Sets and Artificial Neural Networks....Pages 449-470
Genetic Algorithms in Decomposition and Classification Problems....Pages 471-487
Back Matter....Pages 489-601
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