Querying similarity in metric social networks

Abstract. In this paper we tackle the issues of exploiting the concepts of social networking in processing similarity queries in the environment of a P2P network. The processed similarity queries are laying the base on which the relationships among peers are created. Consequently, the com-munities encompassing similar data emerge in the network. The architec-ture of the presented metric social network is formally defined using the acquaintance and friendship relations. Two version of the navigation al-gorithm are presented and thoroughly experimentally evaluated. Finally, learning ability of the metric social network is presented and discussed.