Mining of high average-utility patterns with item-level thresholds

Lin, Jerry Chun-Wei and Li, Ting and Fournier-Viger, Philippe and Zhang, Ji and Guo, Xiangmin (2019) Mining of high average-utility patterns with item-level thresholds. Journal of Internet Technology, 20 (1). pp. 187-194. ISSN 1607-9264


Abstract

In this paper, we introduce a level-wise algorithm named High Average-Utility Itemset Mining with Multiple Minimum Average-Utility threshold (HAUIM-MMAU), which relies on a novel transaction-maximum utility downward closure (TMUDC) property and a concept of least minimum average-utility (LMAU) to mine high average-utility itemsets (HAUIs). Two efficient strategies, named IEUCP and PBCS, are designed to further reduce the search space, and thus speed up the performance of HAUI mining. Several experiments carried out on both synthetic and real-life databases show that the proposed algorithm can efficiently discover the complete set of HAUIs while considering multiple minimum average-utility thresholds.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Published version, in accordance with the copyright policy of the publisher.
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sept 2019 -)
Faculty/School / Institute/Centre: Historic - Institute for Resilient Regions - Centre for Health, Informatics and Economic Research (1 Aug 2018 - 31 Mar 2020)
Date Deposited: 19 Feb 2020 01:26
Last Modified: 24 Feb 2020 04:29
Uncontrolled Keywords: average-utility itemsets, IEUCP, multiple thresholds, PBCS, transaction-maximum utility downward closure
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
Identification Number or DOI: 10.3966/160792642019012001017
URI: http://eprints.usq.edu.au/id/eprint/38126

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