A Ranking Algorithm for Mitigating the Influence of Contrived Ratings on Review Sites

摘要

In this paper, we propose a ranking algorithm for mitigating the influence of contrived ratings by spammers that try to manipulate rankings on review sites. We set a credibility level for each user, which is determined using the Pearson correlation coefficient of the rating given to an object by the user and estimated quality of the object. The estimated quality is the average value of the ratings weighted with the credibility level of raters. We propose a method that uses a provisional estimated quality calculated by eliminating the rating of a user when calculating that user's credibility level. Furthermore, we propose a method that considers the number of ratings given to an object when calculating the estimated quality of the object. Moreover, we demonstrate the superiority of the proposed methods by conducting a comparative experiment using an actual data set.