International Journal of Computational Intelligence Systems

Volume 14, Issue 1, 2021, Pages 1831 - 1841

Research on Comprehensive Evaluation of Data Source Quality in Big Data Environment

Authors
Wenquan Li*, ORCID, Suping XuORCID, Xindong Peng
School of Information Engineering, Shaoguan University, Shaoguan, Guangdong, China
*Corresponding author. Email: 78192128@qq.com
Corresponding Author
Wenquan Li
Received 6 May 2021, Accepted 16 June 2021, Available Online 28 June 2021.
DOI
10.2991/ijcis.d.210622.001How to use a DOI?
Keywords
Big data quality; Analytic hierarchy process (AHP); Entropy method; Comprehensive evaluation; Fuzzy set
Abstract

Data quality is the prerequisite of big data research and the basis of all data analysis, mining, and decision support. Therefore, a comprehensive fuzzy evaluation method for big data quality evaluation is proposed. Through the analysis of big data quality characteristics, a big data quality evaluation system for the whole process of data processing is constructed. The subjective weight and objective weight of each indicator are calculated through the analytic hierarchy process and entropy method. In order to overcome the subjective and one-sided shortcomings of the single weight determination method, the subjective weight and the objective weight are organically integrated through the distance function method to determine the combined weight of each indicator. The quantified result of big data quality is obtained through fuzzy calculation of membership degree. Finally the ranking results of the proposed method are compared with those of some existing multi-attribute decision-making (MADM) methods. The obtained results indicate that the proposed method is reasonable and efficient to deal with MADM problems. It can comprehensively measure the level of big data quality, and provide users with accurate and efficient quality evaluation results.

Copyright
© 2021 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
14 - 1
Pages
1831 - 1841
Publication Date
2021/06/28
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.d.210622.001How to use a DOI?
Copyright
© 2021 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Wenquan Li
AU  - Suping Xu
AU  - Xindong Peng
PY  - 2021
DA  - 2021/06/28
TI  - Research on Comprehensive Evaluation of Data Source Quality in Big Data Environment
JO  - International Journal of Computational Intelligence Systems
SP  - 1831
EP  - 1841
VL  - 14
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.210622.001
DO  - 10.2991/ijcis.d.210622.001
ID  - Li2021
ER  -