Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/2567
Title: Simple association rules (SAR) and the SAR-based rule discovery
Authors: Chen, GQ
Wei, Q
Liu, D
WETS, Geert 
Issue Date: 2002
Publisher: PERGAMON-ELSEVIER SCIENCE LTD
Source: COMPUTERS & INDUSTRIAL ENGINEERING, 43(4). p. 721-733
Abstract: Association rule mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a problem of concern, as conventional mining algorithms often produce too many rules for decision makers to digest. Instead, this paper concentrates on a smaller set of rules, namely, a set of simple association rules each with its consequent containing only a single attribute. Such a rule set can be used to derive all other association rules, meaning that the original rule set based on conventional algorithms can be 'recovered' from the simple rules without any information loss. The number of simple rules is much less than the number of all rules. Moreover, corresponding algorithms are developed such that certain forms of rules (e.g. 'P double right arrow ?' or '? double right arrow Q') can be generated in a more efficient manner based on simple rules. (C) 2002 Elsevier Science Ltd. All rights reserved.
Notes: Tsing Hua Univ, Sch Econ & Management, Beijing 100084, Peoples R China. Univ Texas, Ctr Res E Commerce, Austin, TX 78712 USA. Univ Limburg, B-3590 Diepenbeek, Belgium.Chen, GQ, Tsing Hua Univ, Sch Econ & Management, Beijing 100084, Peoples R China.
Keywords: data mining; KDD; simple association rules
Document URI: http://hdl.handle.net/1942/2567
ISSN: 0360-8352
e-ISSN: 1879-0550
DOI: 10.1016/S0360-8352(02)00135-3
ISI #: 000178152900006
Category: A1
Type: Journal Contribution
Validations: ecoom 2003
Appears in Collections:Research publications

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