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Information granulation and rough set approximation (2001)
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| Venue: | International Journal of Intelligent Systems |
| Citations: | 52 - 19 self |
BibTeX
@ARTICLE{Yao01informationgranulation,
author = {Y. Y. Yao},
title = {Information granulation and rough set approximation},
journal = {International Journal of Intelligent Systems},
year = {2001},
pages = {87--104}
}
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Abstract
Information granulation and concept approximation are some of the fundamental issues of granular computing. Granulation of a universe involves grouping of similar elements into granules to form coarse-grained views of the universe. Approximation of concepts, represented by subsets of the universe, deals with the descriptions of concepts using granules. In the context of rough set theory, this paper examines the two related issues. The granulation structures used by standard rough set theory and the corresponding approximation structures are reviewed. Hierarchical granulation and approximation structures are studied, which results in stratified rough set approximations. A nested sequence of granulations induced by a set of nested equivalence relations leads to a nested sequence of rough set approximations. A multi-level granulation, characterized by a special class of equivalence relations, leads to a more general approximation structure. The notion of neighborhood systems is also explored. 1
Keyphrases
rough set approximation information granulation nested sequence rough set theory standard rough related issue equivalence relation concept approximation coarse-grained view nested equivalence relation multi-level granulation neighborhood system fundamental issue special class general approximation structure corresponding approximation structure hierarchical granulation similar element stratified rough set approximation granulation structure approximation structure
