Improved user similarity computation for finding friends in your locationImproved user similarity computation for finding friends in your location Peer-Reviewed Journal Publication Δημοσίευση σε Περιοδικό με Κριτές 2019-05-232018enRecommender systems are most often used to predict possible ratings that a user would assign to items, in order to find and propose items of possible interest to each user. In our work, we are interested in a system that will analyze user preferences in order to find and connect people with common interests that happen to be in the same geographical area, i.e., a “friend” recommendation system. We present and propose an algorithm, Egosimilar+, which is shown to achieve superior performance against a number of well-known similarity computation methods from the literature. The algorithm adapts ideas and techniques from the recommender systems literature and the skyline queries literature and combines them with our own ideas on the importance and utilization of item popularity. http://creativecommons.org/licenses/by/4.0/Human-Centric Computing and Information Sciences81Tsakalakis_et_al_Hum. Cent. Comput. Inf. Sci._8(1)_2018.pdfChania [Greece]Library of TUC2019-05-21application/pdf1.1 MBfree Tsakalakis Georgios Τσακαλακης Γεωργιος Koutsakis Polychronis Κουτσακης Πολυχρονης Springer Nature [academic journals on nature.com] Recommender systems Similarity Common interests Algorithm Egosimilar+