A multi-core approach to efficiently mine high-utility itemsets in dynamic profit databases

Bay Vo, Loan T.T. Nguyen, Trinh D.D. Nguyen, Philippe Fournier-Viger, Unil Yun
2020 IEEE Access  
Analyzing customer transactions to discover high-utility itemsets is a popular task, which consists of finding the sets of items that are purchased together and yield a high profit. However, many studies assume that transactional data is static while in real-life, it changes over time. For example, the unit profits of items may vary from one week to another because sale prices and production costs may change. Many algorithms for mining high-utility itemsets (HUI) ignore this important property
more » ... important property and thus are inapplicable or generate inaccurate results on real data. To address this issue, this paper proposes a novel algorithm named Multi-Core HUI Miner (MCH-Miner). It adapts techniques introduced in the iMEFIM algorithm to run on a parallel multi-core architecture to efficiently mine HUIs in dynamic transaction databases. An empirical evaluation shows that in most cases, MCH-Miner is significantly faster than iMEFIM, and that the cost of database scans is reduced. Data mining, high utility itemset, dynamic profit, parallel, multithread. 85890 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ VOLUME 8, 2020 INDEX TERMS
doi:10.1109/access.2020.2992729 fatcat:sqx5bb3e7vbwfpdwts72wjqxga