App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 8

Effective incremental mining algorithm for periodic high-utility sequential patterns

Xun Yaling
Ren Ziqian
Yan Haibo
College of Computer Science & Technology, Taiyuan University of Science & Technology, Taiyuan Shanxi 030024, China
DOI: 10.19734/j.issn.1001-3695.2023.12.0607

Abstract

Periodic High Utility Sequential Pattern Mining (PHUSPM) has attracted much attention because it can find more practical regular patterns in time series. However, existing PHUSPM algorithms struggle to effectively handle incremental updates and overlook the downward closure property and complexity of the algorithm in large-scale data. To solve this problem, we propose an IncPUS-Miner algorithm, which effectively realizes the incremental mining of periodic high-utility sequential patterns (PHUSPs) . IncPUS-Miner introduces a novel data structure called pu-tree. Each tree node corresponds to an updated utility list (UUL) to store the auxiliary information of the corresponding sequence. When incremental data is added, this structure allows flexible updates to project information, thereby enhancing the dynamic adaptability and scalability of the algorithm. In addition, two new upper bounds of sequence utility, PUB and EUB, and two corresponding pruning strategies are proposed, which effectively reduce the computational burden. The experimental results show that the IncPUS-Miner algorithm effectively realizes the incremental mining of PHUSPs on real data, and shows superior performance compared with other algorithms.

Foundation Support

国家自然科学基金面上项目(62272336)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.12.0607
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 8

Publish History

[2024-03-07] Accepted Paper

Cite This Article

荀亚玲, 任姿芊, 闫海博. 一种有效的周期高效用序列模式增量挖掘算法 [J]. 计算机应用研究, 2024, 41 (8). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.12.0607. (Xun Yaling, Ren Ziqian, Yan Haibo. Effective incremental mining algorithm for periodic high-utility sequential patterns [J]. Application Research of Computers, 2024, 41 (8). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.12.0607. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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