CLIR model based on a combination of ontology and statistical method

For improving the performance of cross-lingual information retrieval, a hybrid language model is presented based on a combination of ontology and statistical method. In the structure of the language model, an ontology description frame was given and a linguistic ontology knowledge presentation was determined. A linguistic ontology knowledge bank of source language was created, which combines with semantic, pragmatic and syntactic by learning typical corpus. In cross-lingual information retrieval, the initial document set will be obtained by ontology presentation and all documents will be re-ordered based on linguistic ontology knowledge of source language for improving the precision of Top N rank. The cross-lingual information retrieval data set in NTCIR-3 Workshop was used to evaluate the performance of the language model. The results indicate that the proposed method improves the precision of nature language processing.