Interpretations of Association Rules by Granular Computing

Li, Yuefeng & Zhong, Ning (2003) Interpretations of Association Rules by Granular Computing. In Tuzhillin, Wu & Shaulik, - (Eds.) 3rd International conference on Data Mining, 19-22 November, Los Alamitos, California, USA.

Abstract

We present interpretations for association rules. We first introduce Pawlak's method, and the corresponding algorithm of finding decision rules (a kind of association rules). We then use extended random sets to present a new algorithm of finding interesting rules. We prove that the new algorithm is faster than Pawlak's algorithm. The extended random sets are easily to include more than one criterion for determining interesting rules. We also provide two measures for dealing with uncertainties in association rules.

Impact and interest:

23 citations in Scopus
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9 citations in Web of Science®

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ID Code: 11128
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
ISBN: 0769519784
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2003 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 06 Dec 2007 00:00
Last Modified: 29 Feb 2012 12:59

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