NDLI: Approximation spaces in granular computing

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Approximation spaces in granular computing

Content Provider	IEEE Xplore Digital Library
Author	Jianchao Han
Copyright Year	2009
Description	Author affiliation: Department of Computer Science, California Statement University Dominguez Hills, USA (Jianchao Han)
Abstract	Most data mining and granular computing systems extract knowledge or concept patterns from inexact and uncertain contexts. These patterns are usually approximated by a set of certain and exact components or granules. Therefore, research on approximation spaces becomes the bottleneck of granular computing and data mining. A variety of approximation spaces have been proposed and extensively investigated. Some typical approximation spaces are summarized and compared in this paper, including fuzzy sets, rough sets, near sets and neighborhood systems. Their characteristics and application domains are analyzed and compared. These approximation spaces are unified under the framework of neighbor systems.
Starting Page	203
Ending Page	208
File Size	222190
Page Count	6
File Format	PDF
ISBN	9781424448302
DOI	10.1109/GRC.2009.5255129
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Fuzzy sets Rough sets Spatial databases Pattern recognition Data mining Problem-solving Probes Information systems Fuzzy systems
Content Type	Text
Resource Type	Article

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