Research On Web Cross Language Information Retrieval Based On Ontology

With the increasingly rich of network information, people are not satisfied with retrieving in the same kind of language, so Cross-Language Information Retrieval (CLIR) receives people's more and more concern. Although there are already have some CLIR system at present, but they using traditional retrieval strategy, it can only get the information which is literally match, it can not provide the intelligent retrieval based on concept, and its performance are low.The article made deep analysis and study about the segmentation mechanism of Chinese dictionary, method of query translation and retrieval strategy for CLIR. In order to meet the condition that user often enter keywords as query sentences, this paper design an Web cross language information retrieval model based on the domain ontology, using the advantage of ontology in describing things to extend the query, lead the retrieval rise to semantic level. By experiment, it illustrate that the retrieval recall and precision of the model are improved.