Integration of User Profile in Search Process according to the Bayesian Approach

Abstract

Most information retrieval system (IRS) rely on the so called system-centred approach, behaves as a black box, which produces the same answer to the same query, independently on the user’s specific information needs. Without considering the user, it is hard to know which sense refers to in a query. To satisfy user needs, personalization is an appropriate solution to improve the IRS usability. Modeling the user profile can be the first step towards personalization of information search. The user profile refers to his/her interests built across his/her interactions with the retrieval system. In this paper, we present a personalized information retrieval approach for building and exploiting the user profile in search process, based on Bayesian network. The theoretical framework provided by these networks allows better capturing the relationships between different information. Experiments carried out on TREC-1 ad hoc and TREC 2011 Track collections show that our approach achieves significant improvements over a personalized search approach described in the state of the art and also to a baseline search information process that do not consider the user profile