Context-Aware Recommender Systems: A Service-Oriented Approach

Published 1 December 2009

Sofiane Abbar, Mokrane Bouzeghoub, Stéphane Lopez

Citations59

TL;DR

The approach presented is based on a previous work on data personalization which leads to the denition of a Personalized Access Model that provides a set of personalization services and it is shown how these services can be deployed in order to provide advanced context-aware recommender systems.

Abstract

Recommender systems are efficient tools that overcome the information overload problem by providing users with the most relevant contents. This is generally done through user’s preferences/ratings acquired from log files of his former ses-sions. Besides these preferences, taking into account the interaction context of the user will improve the relevancy of recommendation process. In this paper, we propose a context-aware recommender system based on both user pro-file and context. The approach we present is based on a previous work on data personalization which leads to the definition of a Personalized Access Model that provides a set of personalization services. We show how these services can be deployed in order to provide advanced context-aware recommender systems. 1.

Keywords

Computer Science

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