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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 10
2970-2977

Mining high utility itemsets based on statistical significance testing

Wu Jun
Wei Dandan
Ouyang Aijia
Wang Ya
School of Information Engineering, Zunyi Normal University, Zunyi Guizhou 563000, China
DOI: 10.19734/j.issn.1001-3695.2024.01.0027

Abstract

Aiming at the problem of traditional high utility itemset mining algorithms reporting false positive high utility itemsets in transactions with class labels, this paper proposed two high utility itemset mining algorithms called FHUI and PHUI. The FHUI and PHUI firstly found all the candidates and grouped them by length. Then, the FHUI established null distributions with the frequency distributions, while the PHUI established null distributions by the permutation strategy within or between transactions. Finally, the FHUI and PHUI calculated the p values from the null distributions and exploited the false discovery rate to eliminate the false positive high utility itemsets. The experiments on the benchmark data sets show that the FHUI and PHUI can eliminate a large number of false positive itemsets, which allows them to achieve higher accuracy rates in the classification tasks. The experiments on synthetic data sets reveal that the proportions of false positive itemsets reported by FHUI and PHUI are lower than 4.8% and the average utility values are higher than 39 000. Experimental results prove that the statistically significant high utility itemsets reported by the FHUI and PHUI are more reliable and practical in transactions with class labels.

Foundation Support

国家自然科学基金资助项目(62066049)
贵州省教育厅高等学校青年资助项目(黔教技［2022］313,黔教合KY［2022］015)
贵州省科技厅科技支撑计划资助项目(黔科合支撑［2023］257)
遵义市科技合作资助项目(遵市科合HZ字(2022)123)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.01.0027
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 10
Section: Algorithm Research & Explore
Pages: 2970-2977
Serial Number: 1001-3695(2024)10-013-2970-08

Publish History

[2024-04-18] Accepted Paper
[2024-10-05] Printed Article

Cite This Article

吴军, 魏丹丹, 欧阳艾嘉, 等. 基于统计显著性检验的高效用项集挖掘算法 [J]. 计算机应用研究, 2024, 41 (10): 2970-2977. (Wu Jun, Wei Dandan, Ouyang Aijia, et al. Mining high utility itemsets based on statistical significance testing [J]. Application Research of Computers, 2024, 41 (10): 2970-2977. )

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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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