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DISCOVERING BINARY AND FUZZY ASSOCIATION RULES FROM DATABASE

Hoang Kiem 1
Do Phuc 1
Volume & Issue: Vol. 2 No. 11&12 (1999) | Page No.: 5-16 | DOI: 10.32508/stdj.v2i11&12.3691
Published: 1999-12-31

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This article is published with open access by Viet Nam National University, Ho Chi Minh City, Viet Nam. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0) which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

Abstract

In this paper, we propose u method for discovering the binary und fuzzy association rules from database. We study a new kind of association rules: fuzzy association rules. We use the rough set theory of Z. Pawlak und fuzzy set theory of L.A. Zuden for defining some concepts and developing our method bused on these new .concepts. We also introduce un application for discovering the fuzzy rules from a database in supermarket. In this application, we study the quantity of purchused items instead of 'to be purchased or not to be purchased information of a particular item as the traditional approach did.

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