Web Content Trust Rating Prediction Using Evidence Theory

Download Document/Synopsis
You can find number of information on web. Some information on the web can be trusted some may not. In order to find out whether particular information displayed on the web can be trusted or not, we proposed a system where web information is predicted as trustable based on the rating of various users. Here in this system user will read the information displayed on the web and will rate the information. The rating score is used as evidence, based on the ratings of various users system will predict whether the information provided on the web can be trusted or not. This system uses user ratings to infer trust relationships between users. The rating score of the user is used as evidence to find out whether the information displayed on the web is trustable or not. Mining web user trust relationship is important in web information credibility analysis. Motivated by the imprecise nature of trustiness, we propose a novel web user trust prediction method based on evidence theory, which uses user ratings to infer trust relationships between users, where each rating score is treated as evidence. This system will help to built trust between the web users. User can easily trust the content displayed on the website. This system will help to reduce false content to be displayed on web.


Advantages
  • This system will help to built trust between the web users.
  • This system will help to reduce false content to be displayed on web.
  • User can easily trust the content displayed on the website.

Disadvantages
  • This system does not detect those users who had falsely rated.

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