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High Utility Pattern Mining using a Prefix-Tree  

Jeong, Byeong-Soo (경희대학교 전자정보대학 컴퓨터공학)
Ahmed, Chowdhury Farhan (경희대학교 전자정보대학 컴퓨터공학)
Lee, In-Gi (이화대학교 컴퓨터공학과)
Yong, Hwan-Seong (이화대학교 컴퓨터공학과)
Publication Information
Journal of KIISE:Databases / v.36, no.5, 2009 , pp. 341-351 More about this Journal
Abstract
Recently high utility pattern (HUP) mining is one of the most important research issuer in data mining since it can consider the different weight Haloes of items. However, existing mining algorithms suffer from the performance degradation because it cannot easily apply Apriori-principle for pattern mining. In this paper, we introduce new high utility pattern mining approach by using a prefix-tree as in FP-Growth algorithm. Our approach stores the weight value of each item into a node and utilizes them for pruning unnecessary patterns. We compare the performance characteristics of three different prefix-tree structures. By thorough experimentation, we also prove that our approach can give performance improvement to a degree.
Keywords
High utility pattern mining; data mining; transaction frequency; transaction weighted utilization;
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