Improved Strategy for High-Utility Pattern Mining Algorithm
Joint Authors
Wang, Le
Li, Haiyan
Zhou, Chunliang
Wang, Shui
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-26
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
High-utility pattern mining is a research hotspot in the field of pattern mining, and one of its main research topics is how to improve the efficiency of the mining algorithm.
Based on the study on the state-of-the-art high-utility pattern mining algorithms, this paper proposes an improved strategy that removes noncandidate items from the global header table and local header table as early as possible, thus reducing search space and improving efficiency of the algorithm.
The proposed strategy is applied to the algorithm EFIM (EFficient high-utility Itemset Mining).
Experimental verification was carried out on nine typical datasets (including two large datasets); results show that our strategy can effectively improve temporal efficiency for mining high-utility patterns.
American Psychological Association (APA)
Wang, Le& Wang, Shui& Li, Haiyan& Zhou, Chunliang. 2020. Improved Strategy for High-Utility Pattern Mining Algorithm. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1193642
Modern Language Association (MLA)
Wang, Le…[et al.]. Improved Strategy for High-Utility Pattern Mining Algorithm. Mathematical Problems in Engineering No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1193642
American Medical Association (AMA)
Wang, Le& Wang, Shui& Li, Haiyan& Zhou, Chunliang. Improved Strategy for High-Utility Pattern Mining Algorithm. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1193642
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1193642