Recommendation of similar users, resources and social networks in a Social Internetworking Scenario

In this paper we propose an approach to recommend to a user similar users, resources and social networks in a Social Internetworking Scenario. Our approach presents some interesting novelties with respect to the existing ones. First of all, it operates on a Social Internetworking context and not on a single social network. Moreover, it considers not only explicit relationships among users but also the implicit ones, connecting users on the basis of shared interests and behavior; the latter is derived from the analysis of user actions in the considered Social Internetworking Scenario. In addition, it considers the presence of possible semantic anomalies involving the description of available users, resources and social networks. Finally, it takes into account not only the local information regarding involved users, resources and social networks but also the global one, i.e., the information spread all over the considered Social Internetworking Scenario.