Mining disjunctive consequent association rules

Authors:
Ding-An Chiang;Yi-Fan Wang;Yi-Hsin Wang;Zhi-Yang Chen;Mei-Hua Hsu
Affiliations:
Department of Computer Science and Information Engineering, Tamkang University, Taiwan, ROC;Institute of Information Science and Management, National Taipei College of Business, Taiwan, ROC;Department of Information Management, Chang Gung Institute of Technology, Taiwan, ROC;Department of Computer Science and Information Engineering, Tamkang University, Taiwan, ROC;Department of General Education, Chang Gung Institute of Technology, 261, Wen-Hwa 1st Road, Kwei-Shan, Taoyuan, Taiwan, ROC
Venue:
Applied Soft Computing
Year:
2011

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Abstract

When association rules A-B and A-C cannot be discovered from the database, it does not mean that A-B@?C will not be an association rule from the same database. In fact, when A, B or C is the newly marketed product, A-B@?C shall be a very useful rule in some cases. Since the consequent item of this kind of rule is formed by a disjunctive composite item, we call this type of rules as the disjunctive consequent association rules. Therefore, we propose a simple but efficient algorithm to discover this type of rules. Moreover, when we apply our algorithm to insurance policy for cross selling, the useful results have been proven by the insurance company.