A Study On Ontology-based Intelligent Information Retrieval System

Nowadays, Web becomes the main information resource for People. However it is not easy for them to get the really interested information on the Web, since web pages are semi-structure or non-structure, the hyperlinks are disordered and the data are massive, various and dynamic. Traditional information retrieval technology is mainly based on keyword matching and has little semantic inferring ability. Moreover it does not provide semantic guidance for users. So information retrieval System may miss some information that users really want and return some information that users don't want. How to improve the quality and efficiency of information retrieval becomes an important study field of information retrieval (IR), data mining (DM) and knowledge management (KM).The essential method to improve the quality and efficiency of information retrieval is to change disorderly data into orderly knowledge, to make computers understand the web information and the need of people and finally realize semantic information retrieval. Tim Berners-Lee proposed the concept of Semantic Web in 1998. It is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. Ontology provides semantic expression mechanism for Web information and is the key technology of Semantic Web.This paper analyzes the problem and disadvantage of traditional retrievals in Web. Following, this paper makes a deeply research on the concepts, modeling primitives, describing languages, constructing methods, constructing tools of ontology and analyzes the semantic ability of the OWL. Furthermore, a framework of intelligent information retrieval system based on Ontology is proposed. Key techniques have been also deeply studied in this paper. As the theory basis of prototype system, three solutions about Ontology construction, Ontology storage and semantic information retrieval strategy are proposed.