Querying Similarity in Metric Social Networks

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Authors

SEDMIDUBSKÝ Jan

Year of publication 2007
Type R&D Presentation
MU Faculty or unit

Faculty of Informatics

Citation
Description 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 communities encompassing similar data emerge in the network. The architecture of the presented metric social network is formally defined using the acquaintance and friendship relations. Two version of the navigation algorithm are presented and thoroughly experimentally evaluated. Finally, learning ability of the metric social network is presented and discussed.
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