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Sci Eng Ethics. 2018 Oct;24(5):1577-1588. doi: 10.1007/s11948-017-9959-2. Epub 2017 Aug 15.

E-commerce Review System to Detect False Reviews.

Author information

1
Department of Computer Science, College of Arts and Science, Prince Sattam Bin Abdulaziz University, Wadi Ad Dawaser, 11990, Saudi Arabia. manjur.kolhar@gmail.com.

Abstract

E-commerce sites have been doing profitable business since their induction in high-speed and secured networks. Moreover, they continue to influence consumers through various methods. One of the most effective methods is the e-commerce review rating system, in which consumers provide review ratings for the products used. However, almost all e-commerce review rating systems are unable to provide cumulative review ratings. Furthermore, review ratings are influenced by positive and negative malicious feedback ratings, collectively called false reviews. In this paper, we proposed an e-commerce review system framework developed using the cumulative sum method to detect and remove malicious review ratings.

KEYWORDS:

Cloud computing; Cumulative sum; E-commerce; False review rating; Product review

PMID:
28812228
DOI:
10.1007/s11948-017-9959-2
[Indexed for MEDLINE]

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