Research On Information Retrieval Technology Based On Semantic Web

Information explosion is a major characteristic of the current information society. Information Retrieval is an important way for people to acquire knowledge and information. Using the traditional information retrieval method, users are difficult to find the desired resources. How to retrieve the required information becomes a key problem. Semantic information retrieval is a promising way to solve this problem. Under the support of Semantic Web and its theory and technologies, Semantic information retrieval has become a hot spot of recent research.This paper firstly researches the theory of Semantic Web and Ontology and Description Logic. Then on the basic of the theory of Information Retrieval based on Ontology and full-text retrieval based on Lucene, we build one model of Information Retrieval based on Semantic Web and introduce every module function of this semantic retrieval model in detail.This paper deeply studies the key technologies about Semantic Information Retrieval. The key technologies mainly contain the building of domain ontologies, collection of information resource, semantic reasoning, target semantic analysis and semantic similarity analysis. Among these technologies, this paper improves the method of Semantic Analysis of Query Target based on the Keywords, which considers the meaning and semantic association of the keywords. The improved method can improve the completeness and accuracy of mapping the keywords to ontology concept, and effectively infer the users'intention. These feasible technologies provide the good support for the Semantic Information Retrieval Model.At last on the basic of above theory, we develop an experiment Semantic Information Retrieval System for Document-SIRD. In this system we choose paper about computer as the retrieved object and build the relative domain ontologies. By semantic reasoning process, we get the correlation relationship between papers. Therefore we solve the problem of lack of semantic on resource object in the retrieval and make the result meet the need of users. The smooth implementation of Semantic Retrieval system can verify the feasibility of Semantic Information Retrieval Model.