We propose FriendSensing, a framework that automatically suggests friends to mobile social-networking users. Using short-range technologies (e.g., Bluetooth) on her mobile phone, ...
Recommender Systems belong to a class of systems intended to assist individuals make evaluations about entities in meaningful ways. In this paper we discuss the issues in the desi...
Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. While research in rec...
Abstract—This paper proposes LARS, a location-aware recommender system that uses location-based ratings to produce recommendations. Traditional recommender systems do not conside...
Justin J. Levandoski, Mohamed Sarwat, Ahmed Eldawy...
The accuracy of collaborative filtering recommender systems largely depends on two factors: the quality of the recommendation algorithm and the nature of the available item rating...