Research Of Semantic Retrieve Model Based On Semantic Web

Due to traditional information retrieval pattern, the information lacks a uniform semantic description. It is hard for user to find high relevant information and to share information resource semantically. How to assign the managed information resources with a machine understandable meaning and realize the semantic searching by means of the domain knowledge, achieving a high utilization rate of information resources, which are the challenges facing the field of information retrieval. Semantic Web is the next generation Web, which is advocated by Tim Berners-Lee who is one of the founders of the Web. In Semantic Web, every resource has unique identifier, and there exist of semantic relations between resources. Semantic Web is an expansion and extension of Contemporary World Wide Web, in which information resources are expressed in a clear and formal way, can improve the interoperability between heterogeneous systems, promote knowledge sharing. Based on the analysis of the basic principle technology, tool and feature of traditional Web information retrieval technology, the paper proposes a framework of semantic retrieval based on Semantic Web. The design idea and retrieval process of the Semantic Information Retrieval system are described in detail. The rationality of the system framework is also been proofed. The paper gives in-depth analysis of a number of key technologies which are involved in Semantic Information Retrieval System: domain ontology construction, information resource collection, semantic inference, and semantic reasoning ranking of the retrieval result set. These technologies establish the theory basis for implementing of an intelligent retrieval system. Finally, based on the previous theoretical analysis, we have successfully developed a semantic medical search system - OntoSearch (Ontology Search), which related to the field of medicine for semantic information retrieval target and constructs the corresponding domain ontology — Ontology medicine. By mapping the various layers of information to domain ontology and semantic reasoning, the relationships between the resources can be fully exploited; the problem of the shortage of resources of the semantic information retrieval target is fundamentally solved. OntoSearch can meet user demand with more relevant result in the semantic retrieval target resources. OntoSearch also implements the relatively complex knowledge query and secondary search function, provide resources to the area of value-added services. These functions are difficult to achieve based on traditional key words matching retrieval system. Practically, OntoSearch test the feasibility of the Semantic InformationRetrieval System Framework.