Study On Applying Semantic Web To Intelligent Information Retrieve

According to traditional information retrieval pattern, the information lacks a uniform semantic description. It is hard for user to find more relevant information and to realize the semantic share in information resource. How to assign the managed resource a machine understandable meaning so as to find what users really need, and how to realize the semantic searching by means of the domain knowledge, are challenging tasks for information retrieval. Semantic Web is the next generation Web, which is advocated by Tim Berners-Lee who is a founder of the Web. In Semantic Web, every resource has unique identifier, and there are all of semantic relations between resources. The Semantic Web is an extension of current Web in which information is given well-defined meaning and makes computers and people work in cooperation. Have analyzed the principle, technology, tool and feature of traditional retrievals in Web, the paper proposes a framework of intelligent retrieve based on semantic Web. It also describes design idea and process of the intelligent information retrieval system in detail, and proves in theory the validity of the framework. Aims at key techniques of intelligent retrieve system, the paper gives our solutions which establish the theory basis for implement of an intelligent retrieval system. These key techniques include domain ontology construction, information resource collection, semantic inference,and sort of retrieve result set. Based on our theory analysis, we have successfully developed an intelligent paper search system (ISearch). ISearch selects science papers related to computer domain as experiment objects, and builds related domain ontology (paper ontology and semantic dictionary ontology). Compared with traditional key words matching retrieval system, the system can find the internal relationship among resources, and represent user more relevant resource through the mapping from resource layer to ontology layer and the semantic inference process. What's more, the system can realize some complicate knowledge query and value-added service. ISearch proves the correctness of intelligent information retrieval framework in practice.