A collaborative recommendation system for location based social networks

Abstract

We propose a trust-aware collaborative filtering for the recommendation of services in a mobile scenario. We used Jaccard measure to select user's neighborhood containing the most similar users in terms of interests, and exploited the explicit social links existing between users in social networks as trust information, in order to optimize the quality of the neighborhood. We also propose to use an early proposed similarity measure, QSim, to compare profiles.