%0 Journal Article
%A SUN Yue-ping
%A WANG Xiao-jie
%A WANG Xu-wen
%T Cross-Lingual Pseudo Relevance Feedback Based on Bilingual Topics
%D 2013
%R 10.13190/jbupt.201304.81.wangxw
%J Journal of Beijing University of Posts and Telecommunications
%P 81-84
%V 36
%N 4
%X <p>A cross-lingual pseudo relevance feedback model based on bilingual topics is proposed for cross language information retrieval task. The latent Dirichlet allocation (LDA) model is extended to the bilingual topic model, each topic could generate a source language token and a target language token. A strategy on how to choose topics and words for cross language query expansion is given, and the secondary retrieval is performed on the basis of the refined query translation. Experiments show that this model outperforms monolingual LDA-based feedback method as well as classical techniques based on vector space model.</p>
%U https://journal.bupt.edu.cn/EN/10.13190/jbupt.201304.81.wangxw