Toward a User Interest Ontology to Improve Social Network-Based Recommender System

Abstract

This paper aims to improve traditional recommender systems by incorporating information in social networks, including user preferences and influence from social friends. A user interest ontology is developed to make personalized recommendations out of such information. In this paper, we present a preliminary work that sheds light on the role of social networks as sources for the development of recommendation systems. The need for user interest ontology in recommender systems and its importance as a reference to find similar items in social network is also emphasized. Finally, we describe and account for the role of user interest model based on user interest ontology to deal with the lack of semantic information in personalized recommendation system.