A robust ranking algorithm to spamming

¹ Département de Physique, Université of Fribourg - CH-1700 Fribourg, Switzerland
² Web Sciences Center, University of Electronic Science and Technology of China - 610054 Chengdu, PRC

^a zhutou@ustc.edu

Received: 17 December 2010
Accepted: 6 April 2011

Abstract

Ranking problem of web-based rating systems has attracted much attention. A good ranking algorithm should be robust against spammer attack. Here we proposed a correlation-based reputation algorithm to solve the ranking problem of such rating systems where user votes some objects with ratings. In this algorithm, the reputation of a user is iteratively determined by the correlation coefficient between his/her rating vector and the corresponding objects' weighted average rating vector. Comparing with iterative refinement (IR) and mean score algorithm, results for both artificial and real data indicate that the present algorithm shows a higher robustness against spammer attack.