NDLI: Approximation Reduction Based on Similarity Relation

Content Provider	IEEE Xplore Digital Library
Author	Bing Huang Ling Quo Xian-zhong Zhou
Copyright Year	2007
Description	Author affiliation: Nanjing Audit Univ., Nanjing (Bing Huang)
Abstract	Knowledge reduction is one of the most important tasks in rough set theory, and most types of reductions in this area are based on complete information systems. Though one of the extended relations, similarity relation, has been presented in incomplete information systems, which do exist in real world, its reduction approach has not been examined. In this paper, based on similarity relation, the upper and lower approximation reduction are defined in incomplete information systems. The judgment theorems with respect to the consistent sets of the upper and lower approximation reduction are studied, their discernibility matrices are obtained and the approaches of the upper and lower approximation reduction based on discernibility matrices are presented. To overcome its drawback of NP-hard time complexity, two heuristic algorithms based on significance of attributes are proposed.
Starting Page	124
Ending Page	128
File Size	224573
Page Count	5
File Format	PDF
ISBN	9780769528748
DOI	10.1109/FSKD.2007.191
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Knowledge engineering Information science Technology management Automation Heuristic algorithms Engineering management Management information systems Set theory Knowledge management Information systems
Content Type	Text
Resource Type	Article

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