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Algorithm Research & Explore
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3619-3622

Quantitative data mining algorithm based on improved multi-level fuzzy association rules

Zhang Dingxiang1
Zhang Yuejin2
1. College of Computer & Information Engineering, Guizhou University of Commerce, Guiyang 550014, China
2. School of Information Engineering, East China Jiaotong University, Nanchang 330013, China

Abstract

The accuracy of the rule extraction is not high, the algorithm runs long, and it is difficult to meet the needs of the users in extracting rules from a single hierarchy. To solve the above problems, this paper proposed a quantitative data mining algorithm based on the improved multilevel fuzzy association rules. It adopted the high frequency project set, formed the mining process by continuous deepening of the iterative method. This method integrated fuzzyset theory, data mining algorithm and multi-level classification technology to find fuzzy association rules from the transaction data set, and excavated the hidden knowledge of quantitative value information in the multi-layer structured transaction database. It realized the user's customized information mining needs. The experimental results show that the quantitative data mining algorithm based on the improved multilevel fuzzy association rules has a prominent advantage over other algorithms in mining precision and operation time. It can bring new development in the practical application of multilevel association rule extraction.

Foundation Support

国家自然科学基金资助项目(61164013)
贵州省软科学研究计划项目(黔科合体R字[2014]LKS2007)
贵州省教育厅基金资助项目(黔教社发[2010]339)
贵州省普通高等学校智能物联网工程研究中心建设项目(黔教合KY字[2016]016)
贵州省教育厅项目(黔教合KY字[2017]022)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.06.0405
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 12
Section: Algorithm Research & Explore
Pages: 3619-3622
Serial Number: 1001-3695(2019)12-021-3619-04

Publish History

[2019-12-05] Printed Article

Cite This Article

张定祥, 张跃进. 基于改进多层次模糊关联规则的定量数据挖掘算法 [J]. 计算机应用研究, 2019, 36 (12): 3619-3622. (Zhang Dingxiang, Zhang Yuejin. Quantitative data mining algorithm based on improved multi-level fuzzy association rules [J]. Application Research of Computers, 2019, 36 (12): 3619-3622. )

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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