A Platform for Privacy-Preserving Geo-social Recommendation of Points of Interest

Different recommender systems suggest points of interest (POIs) based on data shared through geo-social networks (GSN). These systems are a very useful resource for mobile users, and an important business opportunity for advertisers. However, GSN data (e.g., the check-in of a person in a particular place) may be private information that a user may not want to release outside her social network. Even if the GSN service is trusted, and users´ data is not directly released, an adversary may be able to reconstruct the data of a GSN user by mining the received recommendations. In this demo we will illustrate an implementation of the POI-Ti-Dico platform for privacy-conscious geo-social recommendation of POIs. The platform includes a server-side private recommender system and a mobile application for the Android framework. Recommendations are computed using a very large dataset of real check-ins.