A three-scan algorithm to mine high on-shelf utility itemsets

Authors:
Guo-Cheng Lan;Tzung-Pei Hong;Vincent S. Tseng
Affiliations:
Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan;Department of Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan and Department of Computer Science and Engineering, National Sun Yat-sen University, ...;Department of Computer Science and Information Engineering and Institute of Medical Informatics, National Cheng-Kung University, Tainan, Taiwan
Venue:
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
Year:
2010

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Abstract

In this paper, we handle a new kind of patterns named high on-shelf utility itemsets, which considers not only individual profit and quantity of each item in a transaction but also common on-shelf time periods of a product combination. We propose a three-scan mining approach to effectively and efficiently discover high on-shelf utility itemsets. The proposed approach adopts an itemset-generation mechanism to prune redundant candidates early and to systematically check the itemsets from transactions. The experimental results on synthetic datasets also show the proposed approach has a good performance.