Transactions on Rough Sets VI: Commemorating Life and Work of Zdislaw Pawlak, Part I

by James F. Peters (Editor), Ivo Düntsch (Editor), Jerzy Grzymala-Busse (Editor), Ewa Orlowska (Editor), Lech Polkowski (Editor)

Overview

This volume of the Transactions on Rough Sets commemorates the life and work of Zdzislaw Pawlak (1926-2006), whose legacy is rich and varied. It presents papers that reflect the profound influence of a number of research initiatives by Professor Pawlak, introducing a number of new advances in the foundations and applications of artificial intelligence, engineering, logic, mathematics, and science.

Product Details

ISBN-13:	9783540711988
Publisher:	Springer Berlin Heidelberg
Publication date:	04/12/2007
Series:	Lecture Notes in Computer Science , #4374
Edition description:	2007
Pages:	500
Product dimensions:	6.10(w) x 9.30(h) x 1.20(d)

Table of Contents

Contributed Papers.- Propositional Logics from Rough Set Theory.- Intuitionistic Rough Sets for Database Applications.- An Experimental Comparison of Three Rough Set Approaches to Missing Attribute Values.- Pawlak’s Landscaping with Rough Sets.- A Comparison of Pawlak’s and Skowron–Stepaniuk’s Approximation of Concepts.- Data Preparation for Data Mining in Medical Data Sets.- A Wistech Paradigm for Intelligent Systems.- The Domain of Acoustics Seen from the Rough Sets Perspective.- Rule Evaluations, Attributes, and Rough Sets: Extension and a Case Study.- The Impact of Rough Set Research in China: In Commemoration of Professor Zdzisław Pawlak.- A Four-Valued Logic for Rough Set-Like Approximate Reasoning.- On Representation and Analysis of Crisp and Fuzzy Information Systems.- On Partial Covers, Reducts and Decision Rules with Weights.- A Personal View on AI, Rough Set Theory and Professor Pawlak.- Formal Topology and Information Systems.- On Conjugate Information Systems: A Proposition on How to Learn Concepts in Humane Sciences by Means of Rough Set Theory.- Discovering Association Rules in Incomplete Transactional Databases.- On Combined Classifiers, Rule Induction and Rough Sets.- Approximation Spaces in Multi Relational Knowledge Discovery.- Finding Relevant Attributes in High Dimensional Data: A Distributed Computing Hybrid Data Mining Strategy.- A Model PM for Preprocessing and Data Mining Proper Process.- Monographs.- Lattice Theory for Rough Sets.

Editorial Reviews

From the reviews:

"It consists of 21 contributed papers, and a 90-plus-page monograph, ‘Lattice Theory for Rough Sets’. … would primarily be of interest to researchers and graduate students who are, or would like to be, in the area of rough sets." (Shrisha Rao, Computing Reviews, Vol. 50 (1), January, 2009)

From the Publisher