Approach to Search Result Rankings Based on User Ratings

Abstract

This paper proposed an approach to rank search results based on user ratings, with a subjective approach to the ranking process. Expert groups unique to each user are created to achieve this effect. When no common ratings are available, the expert group is formed based on a model built on the user's social profile, utilizing inductive algorithms such as a polynomial neural network with active neurons. The approach of ranking search results provides a unique order of elements for each user's list of web resources. This effect is achieved by using evaluations from an expert group that is unique to each user, as well as by incorporating each evaluation into the model for calculating final rankings of web resources with its unique weight, calculated based on their previous activity in the system. The resulting ranking model is much more difficult to falsify because it is based on subjective factors. The ranking model will be unique for each user. Falsifying it would require reproducing the preferences of each user, which is much more difficult than acquiring links to one's web resource from authoritative sources.