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Rough Sets and Rough Logic: A KDD Perspective

Profile image of Lech PolkowskiLech Polkowski

2000, Studies in Fuzziness and Soft Computing

https://doi.org/10.1007/978-3-7908-1840-6_13
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62 pages

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Abstract

Basic ideas of rough set theory were proposed by Zdzis law Pawlak in the early 1980's. In the ensuing years, we have witnessed a systematic, world-wide growth of interest in rough sets and their applications.

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Andrzej S.

Information Sciences, 2007

Worldwide, there has been a rapid growth in interest in rough set theory and its applications in recent years. Evidence of this can be found in the increasing number of high-quality articles on rough sets and related topics that have been published in a variety of international journals, symposia, workshops, and international conferences in recent years. In addition, many international workshops and conferences have included special sessions on the theory and applications of rough sets in their programs. Rough set theory has led to many interesting applications and extensions. It seems that the rough set approach is fundamentally important in artificial intelligence and cognitive sciences, especially in research areas such as machine learning, intelligent systems, inductive reasoning, pattern recognition, mereology, knowledge discovery, decision analysis, and expert systems. In the article, we present the basic concepts of rough set theory and point out some rough setbased research directions and applications.

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The First International Workshop on Rough Sets: State of the Art and Perspectives
Wojciech Ziarko

Ai Magazine

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