A Study On Intelligent Information Retrieval Based On The Semantic Web Technology

With the rapid development of Internet, Web has been the best important information resource. As an essential tool to search for information, the search engine provides a convenient shortcut for users to retrieve that information. However, due to lacking a powerful semantic model, traditional search engines can only adopt the shallow, keyword-based approach. This severely limits their abilities in the intelligent application. The field of information retrieval is confronted with the challenge that how to make the information resource possess the meaning of application program-understandable, meanwhile implement the semantic retrieval and improve the utilization efficiency of information resource according to the knowledge it possess.The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. The goal of the Semantic Web is a vision: the idea of having data on the Web defined and linked in a way that it can be used by machines not just for display purpose, but for automation, integration and reuse of data across various applications.To aim at the weakness in the traditional information retrieval, we combine the traditional information retrieval approach with RDF, RDFS and the web ontology language (OWL) in the Semantic Web, and propose a model of intelligent information retrieval based on the OWL. In support of the search engine technology, the model attempts to achieve semantic query in document repositories. Those documents were descripted by OWL and stored in the knowledge base. This model applies to help the users how to acquire information resource quickly and precisely in the current web; Meanwhile, considering both semantic and keyword-based search comprehensively, we designe the similarity measure algorithm so that the model can work like traditional search engine when knowledge base is incompleteness...