中文版 | English
Title

An efficient utility-list based high-utility itemset mining algorithm

Author
Corresponding AuthorFang, Wei
Publication Years
2022-07-01
DOI
Source Title
ISSN
0924-669X
EISSN
1573-7497
Volume53Issue:6Pages:6992-7006
Abstract
High-utility itemset mining (HUIM) is an important task in data mining that can retrieve more meaningful and useful patterns for decision-making. One-phase HUIM algorithms based on the utility-list structure have been shown to be the most efficient as they can mine high-utility itemsets (HUIs) without generating candidates. However, storing itemset information for the utility-list is time-consuming and memory consuming. To address this problem, we propose an efficient simplified utility-list-based HUIM algorithm (HUIM-SU). In the proposed HUIM-SU algorithm, the simplified utility-list is proposed to obtain all HUIs effectively and reduce memory usage in the depth-first search process. Based on the the simplified utility-list, repeated pruning according to the transaction-weighted utilisation (TWU) reduces the number of items. In addition, a construction tree and compressed storage are introduced to further reduce the search space and the memory usage. The extension utility and itemset TWU are then proposed to be the upper bounds, which reduce the search space considerably. Extensive experimental results on dense and sparse datasets indicate that the proposed HUIM-SU algorithm is highly efficient in terms of the number of candidates, memory usage, and execution time.
Keywords
URL[Source Record]
Indexed By
SCI ; EI
Language
English
SUSTech Authorship
Others
Funding Project
National Key R&D Program of China["2017YFC1601000","2017YFC1601800"] ; National Natural Science foundation of China["62073155","62106088","61673194","61672263"]
WOS Research Area
Computer Science
WOS Subject
Computer Science, Artificial Intelligence
WOS Accession No
WOS:000824373500003
Publisher
EI Accession Number
20222912386067
EI Keywords
Decision making ; Digital storage
ESI Classification Code
Data Storage, Equipment and Techniques:722.1 ; Data Processing and Image Processing:723.2 ; Management:912.2
ESI Research Field
ENGINEERING
Scopus EID
2-s2.0-85134351417
Data Source
Web of Science
Citation statistics
Cited Times [WOS]:2
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/356177
DepartmentDepartment of Computer Science and Engineering
Affiliation
1.Wuxi Inst Technol, Sch Internet Things, Gaolang Rd, Wuxi 214121, Jiangsu, Peoples R China
2.Jiangnan Univ, Jiangsu Prov Engn Lab Pattern Recognit & Computat, Lihu Ave, Wuxi 214122, Jiangsu, Peoples R China
3.Western Norway Univ Appl Sci, Dept Comp Sci Elect Engn & Math Sci, Bergen, Norway
4.Southern Univ Sci & Technol, Comp Sci & Engn Dept, Shenzhen, Peoples R China
Recommended Citation
GB/T 7714
Cheng, Zaihe,Fang, Wei,Shen, Wei,et al. An efficient utility-list based high-utility itemset mining algorithm[J]. APPLIED INTELLIGENCE,2022,53(6):6992-7006.
APA
Cheng, Zaihe,Fang, Wei,Shen, Wei,Lin, Jerry Chun-Wei,&Yuan, Bo.(2022).An efficient utility-list based high-utility itemset mining algorithm.APPLIED INTELLIGENCE,53(6),6992-7006.
MLA
Cheng, Zaihe,et al."An efficient utility-list based high-utility itemset mining algorithm".APPLIED INTELLIGENCE 53.6(2022):6992-7006.
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