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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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
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      pub: Springer Nature
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        au: Kolhar, Manjur
        affil: Department of Computer Science, College of Arts and Science, Prince Sattam Bin Abdulaziz University, 11990, Wadi Ad Dawaser, Saudi Arabia
      su:
        Electronic commerce
        Websites
        Consumers' reviews
        Social media
        Consumer behavior
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          Electronic commerce
          Websites
          Consumers' reviews
          Social media
          Consumer behavior
      keyword:
        Cloud computing
        Cumulative sum
        E-commerce
        False review rating
        Product review
      ab: 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.
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      doctype: Article
      src: R
    language: English
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