Rough Sets in Knowledge Discovery 2

Applications, Case Studies and Software Systems

By: Lech Polkowski (Editor)

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Hardcover | 20 August 1998

At a Glance

Hardcover
616 Pages

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25.4 x 17.78 x 3.33

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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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You Can Find This Book In

Non-Fiction Computing & I.T.Databases Mathematics Mathematical Foundation Set Theory Computer Science Artificial Intelligence Expert Systems & Knowledge-Based Systems Mathematical Logic Applied Mathematics Fuzzy Set Theory

Business & Management Business Mathematics & Systems

Foreword
Introducing the Book	p. 1
Rough Approximation of a Preference Relation in a Pairwise Comparison Table	p. 13
Learning Decision Rules from Similarity Based Rough Approximations	p. 37
Discovery of Data Patterns with Applications to Decomposition and Classification Problems	p. 55
Answering Non-Standard Queries in Distributed Knowledge-Based Systems	p. 98
Approximation Spaces, Reducts and Representatives	p. 109
Data Mining: A Probabilistic Rough Set Approach	p. 127
Soft Processing of Audio Signals	p. 147
A Rough Set Approach to Information Retrieval	p. 166
Extraction Method Based on Rough Set Theory of Rule-Type Knowledge from Diagnostic Cases of Slope-Failure Danger Levels	p. 178
Soft Computing-Based Recognition of Musical Sounds	p. 193
Rough Sets in Industrial Applications	p. 214
Rough Sets in Economic Applications	p. 238
Multistage Rough Set Analysis of Therapeutic Experience with Acute Pancreatitis	p. 272
Reduction Methods for Medical Data	p. 295
Formalization and Induction of Medical Expert System Rules Based on Rough Set Theory	p. 307
Rough Sets for Database Marketing	p. 324
A New Halftoning Method Based on Error Diffusion with Rough Set Filtering	p. 336
IRIS Revisited: A Comparison of Discriminant and Enhanced Rough Set Data Analysis	p. 345
Applications of Rough Patterns	p. 369
Time and Clock Information Systems: Concepts and Roughly Fuzzy Petri Net Models	p. 385
The Synthesis Problem of Concurrent Systems Specified by Dynamic Information Systems	p. 418
Rough Sets and Artificial Neural Networks	p. 449
Genetic Algorithms in Decomposition and Classification Problems	p. 471
Rough Set Bibliography	p. 491
Software Systems
Grobian	p. 555
RSDM: Rough sets Data Miner, A System to Add Data Mining Capabilities to RDBMS	p. 558
LERS - A Knowledge Discovery System	p. 562
TRANCE: A Tool for Rough Data Analysis, Classification, and Clustering	p. 566
ProbRough - A System for Probabilistic Rough Classifiers Generation	p. 569
The ROSETTA Software System	p. 572
RSL - The Rough Set Library	p. 577
Rough Family - Software Implementation of the Rough Set Theory	p. 581
TAS: Tools for Analysis and Synthesis of Concurrent Processes Using Rough Set Methods	p. 587
RoughFuzzyLab - A System for Data Mining and Rough and Fuzzy Sets Based Classification	p. 591
PRIMEROSE	p. 594
KDD-R: Rough Sets-Based Data Mining System	p. 598
Table of Contents provided by Blackwell. All Rights Reserved.

Rough Sets in Knowledge Discovery 2

Applications, Case Studies and Software Systems

At a Glance

Hardcover

Shipping

How to return your order

Defective items

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