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UBP-Miner: An efficient bit based high utility itemset mining algorithm
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AI
DOI：10.1016/j.knosys.2022.108865.png)
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Abstract
En 中文
HUIM (High utility itemset mining) is a key problem in data mining. The goal is to find itemsets having a high importance or profit in a database, to identify useful knowledge that can support decision making. In recent years, many HUIM algorithms have been put forward. Among them, utility-list-based algorithms have become very popular as they are easily extendable and efficient. Although several improvements were made, efficiency remains a critical issue. To address this problem, this paper proposes to improve the utility-list construction process, a key operation that has not been much studied in prior work. A novel set of bitwise operations is proposed called BEO (Bit mErge cOnstruction) to speed up the construction process. Besides, a novel data structure called UBP (Utility Bit Partition) is designed to support BEO. This structure is integrated into a novel UBP-Miner algorithm, which also applies several search space reduction strategies. Experimental results show that UBP-Miner is faster than several state-of-the-art algorithms such as HUI-Miner* and ULB-Miner on common benchmark datasets.(C) 2022 Elsevier B.V. All rights reserved.
Keywords:
Pattern mining
High utility itemset
Utility list buffer
Bitwise operations
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