Non-personalized ranking systems that average the ratings of individual users are prone to attacks associated with bribing. Grouping users according to their preferences and weighting the average by the reputation of the users allows to generate more personalized rankings. These rankings are also less prone to attacks. In a paper published in the ACM Transactions …