Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 1
88-92

Association rule mining algorithm using improving treap with interpolation algorithm in large database

Xin Chunhua
Guo Yanguang
Lu Xiaobo
Dept. of Computer Technology & Information Management, Inner Mongolia Agricultural University, Baotou Inner Mongolia 014109, China
DOI: 10.19734/j.issn.1001-3695.2019.11.0613

Abstract

The explosive growth of information makes the process of data mining and analysis more difficult. It is very difficult for the common association rules mining algorithm to evaluate and discover the relationship between variables in large database under the premise of short running time and low correlation degree. This paper presented an algorithm for mining association rules in large databases based on improved treap. Firstly, the algorithm calculated the priority of each variable in the database. Then, it constructed the treap data structure by the interpolation algorithm to improve build-treap program in the priority model. Finally, it found the relationship of the database by traversing the program and generateRule program. After the stability analysis of the proposed algorithm, the simulation results show that the proposed algorithm can mine the O(n log n) times and O(n2) times in the worst-case analysis and the best-case analysis, respectively. The algorithm can complete the task of variable relational mining in a large database with low correlation degree in a short time, which is much better than the traditional Apriori algorithm and FP growth algorithm.

Foundation Support

国家自然科学基金资助项目(31660602,31660701,31960361)
内蒙古自然科学基金资助项目(2017BS403)
内蒙古自治区高等学校科学研究项目(NJZY20055)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.11.0613
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 1
Section: Algorithm Research & Explore
Pages: 88-92
Serial Number: 1001-3695(2021)01-017-0088-05

Publish History

[2021-01-05] Printed Article

Cite This Article

辛春花, 郭艳光, 鲁晓波. 大型数据库中利用强化学习改进treap的关联规则挖掘算法 [J]. 计算机应用研究, 2021, 38 (1): 88-92. (Xin Chunhua, Guo Yanguang, Lu Xiaobo. Association rule mining algorithm using improving treap with interpolation algorithm in large database [J]. Application Research of Computers, 2021, 38 (1): 88-92. )

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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