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Semi-supervised Learning with Ensemble Method for Online Deceptive Review Detection

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  • Priyanka Shinde
  • Hemlata Channe

Abstract

Now-a-days not only organizers but users also prefer to give opinion after using any kind of resource. Opinion of user is very important for business. Because of opinion of actual user further consumers should think to use that resource. In Business, opinion review has great impact to economical bottom line. Unsurprisingly, opportunistic individuals or groups have attempted to abuse or manipulate online opinion reviews (e.g., spam reviews) so that they credit or degrade the target product. Because of this detecting deceptive and fake opinion reviews is a topic of ongoing research interest. In this paper semi-supervised learning approach with ensemble learning methods is used for finding out these spam reviews. Utility is demonstrated using a data set of online hotel booking websites.

Suggested Citation

  • Priyanka Shinde & Hemlata Channe, 2018. "Semi-supervised Learning with Ensemble Method for Online Deceptive Review Detection," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 3(6), pages 415-422, July.
    • Handle: RePEc:jbh:ijsrcs:v3:y2018:i6:id:hcseit183627
    Note: Article URL: https://ijsrcseit.com/CSEIT183627
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