Polar: Social Recommendation for Context-Aware Mobile Services

Nowadays, several location-based services (LBS) allow their users to take advantage of infor- mation from the Web about points of interest (POIs) such as cultural events or restaurants. To the best of our knowledge, however, none of these provides information taking into account user preferences, or other elements, in addition to location, that contribute to define the context of use. The provided suggestions do not consider, for example, time, day of week, weather, user activity or means of transport. Our work aims at developing social recommender systems able to identify user preferences and information needs, thus suggesting personalized recommendations related to POIs in the surroundings of the user current location.

The proposed systems achieve the following goals:

  1. To supply, unlike the current LBSs, a methodology for identifying user preferences and needs to be used in the information filtering;
  2. To exploit the ever-growing amount of information from social networking, user reviews, and local search Web sites;
  3. To establish procedures for defining the context of use to be employed in the recommendation of POIs with low effort. The flexibility of the architecture is such that our approaches can be easily extended to any category of POI.

Short description of the project (in Italian) on this page.


  • BIANCALANA C., GASPARETTI F., MICARELLI A., SANSONETTI G.. An Approach to Social Recommendation for Context-Aware Mobile Services. ACM Transactions on Intelligent Systems and Technology (TIST), 2013, Vol. 4, No. 1 (PDFBibtex, ©ACM, 2012. This is the author’s version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version will be published in ACM DL)
  • BIANCALANA C., FLAMINI A., GASPARETTI F., MICARELLI A., MILLEVOLTE S., SANSONETTI G.. Enhancing Traditional Local Search Recommendations with Context-Awareness. User Modeling, Adaption and Personalization. Lecture Notes in Computer Science, 2011, Volume 6787/2011, pp335-340 (Preprint PDF, The original publication is available at www.springerlink.com). Bibtex.