Carlos Eduardo Pires

Clustering Peers in Semantic Communities: Putting Together Semantically Similar Peers According to Their Exported Schema Carlos Eduardo Pires

Peer Data Management Systems (PDMSs) are advanced P2P applications in which each peer represents an autonomous data source making available an exported schema to be shared with other peers. The most studied data management issues on PDMSs are related to schema mappings and query answering. These issues can be improved if peers are efficiently disposed in the overlay network. In this context, the notion of semantic community in PDMSs is of great importance since it aims at logically approximating peers with common interests about a specific domain. Due to the dynamic behavior of peers in P2P systems, the management of semantic communities is a challenging issue in the current stage of development of PDMSs. This work proposes an ontology-based process to cluster semantically similar peers in a PDMS. Peers are organized according to their corresponding exported schema (an ontology) and ontology management services are used to assist peer connection. Experimental results on peer clustering are presented and discussed.