A Cross Language Information Retrieval Model Based on Latent Semantic Analysis
S Li · Advances in transdisciplinary engineering · 2024
Aiming at the problems of traditional query expansion methods, a cross language information retrieval scheme based on latent semantic analysis(LSA) was proposed. The method based on SVD and matrix decomposition was used to model wholeheartedly. Then, different types of information were introduced to the singular value decomposition process to analyze the local features and similarity of feature words. Finally, text clustering was applied to the interactive process of retrieval to improve the quality of information retrieval. The experimental results showed that the text retrieval strategy based on latent semantics proposed in this paper effectively improved and optimized the effect of cross language text classification and retrieval. Compared with the traditional algorithm, it had a great improvement in the accuracy index of retrieval.