Transactions on Rough sets III
Author(s)
Bibliographic Information
Transactions on Rough sets III
（Lecture notes in computer science, 3400）
Springer, c2005
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On cover: James F. Peters, Andrzej Skowron, editors-in-chief
On cover: Journal subline
Includes bibliographies and index
Description and Table of Contents
Description
Volume III of the Transactions on Rough Sets (TRS) introduces advances in the theory and application of rough sets. These advances have far-reaching impli- tions in a number of researchareas such as approximate reasoning, bioinform- ics,computerscience,datamining,engineering(especially,computerengineering and signal analysis), intelligent systems, knowledge discovery, pattern recog- tion,machineintelligence,andvariousformsoflearning. This volumerevealsthe vigor, breadth and depth in research either directly or indirectly related to the rough sets theory introduced by Prof. Zdzis law Pawlak more than three decades ago. Evidence of this can be found in the seminal paper on data mining by Prof. Pawlak included in this volume. In addition, there are eight papers on the theory and application of rough sets as well as a presentation of a new version of the Rough Set Exploration System (RSES) tool set and an introduction to the Rough Set Database System (RSDS). Prof. Pawlak has contributed a pioneering paper on data mining to this v- ume. In this paper, it is shown that information ?ow in a ?ow graph is governed by Bayes' rule with a deterministic rather than a probabilistic interpretation.
A cardinal feature of this paper is that it is self-contained inasmuch as it not only introduces a new viewof information?owbut alsoprovidesanintroduction to the basic concepts of ?ow graphs. The representation of information ?ow - troduced in this paper makes it possible to study di?erent relationships in data and establishes a basis for a new mathematical tool for data mining. Inadditionto thepaperbyProf.
Table of Contents
Regular Papers.- Flow Graphs and Data Mining.- The Rough Set Exploration System.- Rough Validity, Confidence, and Coverage of Rules in Approximation Spaces.- Knowledge Extraction from Intelligent Electronic Devices.- Processing of Musical Data Employing Rough Sets and Artificial Neural Networks.- Computational Intelligence in Bioinformatics.- Rough Ethology: Towards a Biologically-Inspired Study of Collective Behavior in Intelligent Systems with Approximation Spaces.- Approximation Spaces and Information Granulation.- The Rough Set Database System: An Overview.- Rough Sets and Bayes Factor.- Formal Concept Analysis and Rough Set Theory from the Perspective of Finite Topological Approximations.- Dissertations and Monographs.- Time Complexity of Decision Trees.
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