In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
See More
Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 10
2987-2992

Cleaning inconsistent data based on statistical inference

Zhang Anzhen1,2
Hu Shengji2
Xia Xiufeng2
1. Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China
2. School of Computer Science, Shenyang Aerospace University, Shenyang 110136, China
DOI: 10.19734/j.issn.1001-3695.2024.02.0055

Abstract

Inconsistent data repair is an important research direction in the field of data repair. Most of the existing methods are based on integrity constraint rules and use the principle of minimum cost for repair. However, the repair scheme with the minimum cost is usually incorrect, which leads to the low accuracy rate of the existing repair methods. To address the problem of low accuracy of existing methods, this paper proposed an inconsistent data repair method based on statistical inference BayesOUR, to balance the cost and quality of repair and improve the repair accuracy. It mainly divided BayesOUR into three phases. Firstly, it performed error detection based on the integrity constraint rule, and then utilized Bayesian network to reason about the probability of all the possible consistent repair schemes. Finally, it selected the repair scheme with the largest probability for data repair. Experimental results on real data show that the method in this paper can significantly improve the accuracy of inconsistent data repair compared with the current leading methods.

Foundation Support

国家自然科学基金青年基金资助项目(6210071734)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.02.0055
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 10
Section: Algorithm Research & Explore
Pages: 2987-2992
Serial Number: 1001-3695(2024)10-015-2987-06

Publish History

[2024-07-05] Accepted Paper
[2024-10-05] Printed Article

Cite This Article

张安珍, 胡生吉, 夏秀峰. 基于统计推理的不一致数据清洗方法 [J]. 计算机应用研究, 2024, 41 (10): 2987-2992. (Zhang Anzhen, Hu Shengji, Xia Xiufeng. Cleaning inconsistent data based on statistical inference [J]. Application Research of Computers, 2024, 41 (10): 2987-2992. )

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.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)