Personalized Web Page Ranking Using Trust and Similarity

Search engines, like Google, use link structure to rank web pages. Although this approach provides an objective global estimate of the web page importance, it is not targeted to the specific user preferences. This paper presents a novel approach for the personalization of the results of a search engine based on the user´s taste and preferences. The concepts of trust and similarity, captured from explicit user input and implicit user behavioral patterns, are used to compute personalized page rankings.