Open Source Recommendation Systems for Mobile Application

The aim of Recommender Systems is to suggest useful items to users. Three major techniques can be highlighted in these systems: Collaborative Filtering, Content-Based Filtering and Hybrid Filtering. The collaborative method proposes recommendations based on what a group of users have enjoyed and it is widely used in Open Source Recommender Systems. The work presented in this paper takes place in the context of SoliMobile Project that aims to design, build and implement a package of innovative services focused on the individual in unstable situation (unemployment, homeless, etc.). In this paper, we present a study of open source recommender systems and their usefulness for SoliMobile. The paper also presents how our recommender system is fed by extracting implicit ratings using the techniques of Web Usage Mining.