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With the increasingly popularity of Q & A Community, it has become an important means for people to re- trieve question from question library to find the answer. Similarity calculation is the core issue in Q & A community, and the appropriate calculation method is the key factor that affects the quality of question retrieval. This paper proposes a re- trieval method based on PLSA model. Firstly, we modelled the question library, and got the probability distribution of "question document -latent semantic -word". Secondly, we calculated the semantic similarity between questions and clas- sify them. Finally, based on user retrieval content, we calculated the similarity between question documents and query, then the query results will be returned to the user in descending order according to the value. Compared with other simi- larity calculation methods that use VSM, HNS and SD, the experimental results show that this proposed method has a high precision rate.

Question Retrieval Based on Probabilistic Latent Semantic Analysis in Q & A Community