E-commerce Review System to Detect False Reviews.

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 f...

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Bibliographic Details
Published in:Science & Engineering Ethics Vol. 24; no. 5; pp. 1577 - 1589
Main Author: Kolhar, Manjur
Format: Article
Published: Springer Nature Oct2018
Subjects:
Online Access:View this record in EBSCOhost
Description
Summary: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.