Strategy Study On Cross-community Semantic Retrieval In Peer-to-Peer Networks

As self-organization, dispersion and openness characteristics of Unstructured P2P network, it has become a hot research topic in academic domain, this paper studied applications of P2P technology in information retrieval, in hope that resources can been better share between the nodes in P2P network. Based on the common interests and demands, peer nodes in P2P network are easy to form a virtual community. As there are often multiple users with similar interests in social networks, P2P network also has this feature, it can be used to position resource rapidly.Firstly this paper systematically arrange the methods of information retrieval in P2P networks among current scholars, summarizes their disadvantages, and based on the demands of node users that across communities retrieval, explain significance with cross-community P2P semantic retrieval.Then this paper analyzes three common P2P community search strategy, namely the general search strategy, P2P retrieval strategy accompanying historical queries records across community and P2P retrieval strategy based on double community structure. It starts from the characteristics of P2P virtual community, through the establishment of hierarchy relationship between community, to lead the retrieval strategy which this paper proposed, namely mining all levels of user’s local resources and search history, forming a cross community routing module, the query is sent to the these nodes, enhanced the accuracy of positioning. At the same time, while interacting cross community, there are heterogeneous ontology among communities.Through the establishment of heterogeneous ontology mapping model, it can ensure the interaction validity of nodes across the community.Finally, according to this ideology, it put forward a P2P semantics retrieval strategy and model across communities, and analyses the realization of each function module. In addition, P2P query expansion based on the traditional keyword have defects that partial interpretation on semantic information of user retrieval. This paper proposes a P2P semantic query expansion method, combining the key relation table and ontology, to achieve a personalized query expansion.