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The product quality risk assessment of e-commerce by machine learning algorithm on spark in big data environment.
- Source :
-
Journal of Intelligent & Fuzzy Systems . 2019, Vol. 37 Issue 4, p4705-4715. 11p. - Publication Year :
- 2019
-
Abstract
- In order to pre-warning the product quality risk of the e-commerce platform, this paper studies the machine learning algorithm for the products quality risk assessment, which propose the Fuzzy C-Means clustering algorithm for the feature extraction and the Cost Sensitive Leaning (CSL)-Naive Bayesian algorithm to construct the assessment model for E-commerce product quality risk form the massive and unbalanced data. The experimental results show that the Machine Learning algorithm based on Spark has better scalability and superiority in the large-scale data environment, which can accurately identify e-commerce product quality risk. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10641246
- Volume :
- 37
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Journal of Intelligent & Fuzzy Systems
- Publication Type :
- Academic Journal
- Accession number :
- 139366263
- Full Text :
- https://doi.org/10.3233/JIFS-179305