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UBP-Miner: An efficient bit based high utility itemset mining algorithm

delete2022-07-01
delete24
PRE
AI
P
Peng Wu
X
Xinzheng Niu *
P
Philippe Fournier‐Viger
C
Cheng Huang
王兵 cover
王兵 (Bing Wang)
DOI:10.1016/j.knosys.2022.108865delete
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Abstract

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

Journal

K
Knowledge-Based Systems
IF:
7.6
Papers:
1.3W
Citations:
4.5W

Organization

S
Southwest Petroleum University
Scholars:
1.4W
Papers: 7.9K
Citations: 8.5K
S
shenzhen university
Scholars:
4.6W
Papers: 3.4W
Citations: 72
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