Research And Implementation Of Intelligent Search Engine Based On Ontology

Search engine as information navigation and the entrance of searches, a growing number of applications is applied to the Internet or the actual field. As users search, the efficiency of search engines becomes one of the important evaluation criteria to guide the development of the search engine. Based on the traditional text retrieval search engine has been gradually be eliminated, and the intelligent search engines which can very good understand of the needs of users have become the focus of the present study.This thesis first discusses the tendency of search engines towards intelligence, indicating that the solution to the inefficiency of traditional search engines lies in improving engines' ability to process and semantically understand the information. Then, on the basis of the study of the Ontology and relevant theories and technologies, the ability of the Ontology to construct semantic models is applied to the research on the intelligence of search engines, with a systematic framework of intelligent search engines based on the Ontology put forward. This framework carries out knowledge retrieval of information by ontologically tagging the collected information and ontologizing what is enquired after the interactive information communication between the user and the computer. It is composed mainly of 4 parts: website crawling, preprocessing, enquiring and processing, and ontological processing. This paper studies the real-time spider crawling strategy, ontological tagging of websites, the establishment of ontology metadata inverted sort table, the ontological expression and ontological match of users'enquiry and several other aspects. Finally, this thesis makes a comparison between this framework's operating result and that of traditional ones, which is followed by the discussion over the reasons. This part indicates that this systematic framework can better understand users'enquiry request and is able to semantically process collected website information, thus increasing the level of the automation and intelligence of search engines and improving the searching efficiency.