Construction of Chinese-English Cross-language Information Retrieval Model Based on Dictionary Learning

Abstract

Using the method of semantic ontology information fusion, this paper obtains the distribution fusion model of Chinese and English cross-language information from the perspective of systemic functional linguistics. A data distributed structure model of Chinese and English cross-language information under Systemic Functional Linguistics is constructed. Structural semantic hierarchical feature analysis method is used to fuse Chinese and English cross-language information under Systemic Functional Linguistics, feature extraction of Chinese and English cross-language information under Systemic Functional Linguistics is carried out in the reorganized feature space, and a fuzzy clustering model of Chinese and English cross-language information retrieval under Systemic Functional Linguistics is established by combining big data mining method. According to the semantic extension of verb-resultative phrases and dictionary learning results, the feature matching of Chinese and English cross-language data in personalized retrieval under the vision of Systemic Functional Linguistics is realized, and the Chinese and English cross-language information retrieval model under the vision of Systemic Functional Linguistics is established by adopting the method of grammatical attribute matching of semantic factors. Tests show that this method has higher accuracy and better matching in cross-language information retrieval between Chinese and English under the vision of Systemic Functional Linguistics.