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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Detalles Bibliográficos
Publicado en:Science & Engineering Ethics Vol. 24; no. 5; pp. 1577 - 1589
Autor principal: Kolhar, Manjur
Formato: Artículo
Publicado: Springer Nature Oct2018
Materias:
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario: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.