A context-aware weighting approach for big data of quality ratings in E-commerce

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  • 1. Department of Computer Science and Technology, Nanjing University, Nanjing 210093, China; 2. School of Information Science and Engineering, Qufu Normal University, Rizhao 276826, Shandong, China

Received date: 2015-11-30

  Online published: 2016-02-29

Abstract

With the fast development of E-commerce, large amounts of quality rating data for commodities are generated online. By analyzing the rating data, users can evaluate the commodities’quality. However, due to the massiveness and diversity of the rating data, it is a challenge for users to evaluate the commodity quality quickly and accurately. To this end, a context-aware weighting approach for E-commerce ratings, context-aware weighting approach (CWA) is proposed. With CWA, a few important rating data are selected and most unimportant data dropped. Thus the commodity quality can be evaluated quickly and accurately. A series of experiments validate effectiveness of the proposed CWA.

Cite this article

QI Lianyong1,2, DOU Wanchun1, ZHOU Yuming1 . A context-aware weighting approach for big data of quality ratings in E-commerce[J]. Journal of Shanghai University, 2016 , 22(1) : 36 -44 . DOI: 10.3969/j.issn.1007-2861.2015.04.021

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