问答社区中候选答案过多会增加提问用户选择最佳答案的负担.为此,提出一种基于概率潜在语义分析(PLSA)模型的自动答案选择方法.在主题建模思想的基础上,利用问答社区中的用户资料,以PLSA模型表达问答社区中的用户兴趣分布,依据答案和问题之间的主题匹配度对候选答案进行排序.实验结果表明,该方法可有效挖掘用户兴趣,提高答案选择的准确率.析;主题建模%A novel answer selection method based on topic modeling techniques is proposed to mitigate the issue of question asker's burden of selecting the best answer stemming from too many candidate answers in question answering communities.Aiming at the problem, this paper presents an automatic answer selection based on Probabilistic Latent Semantic Analysis(PLSA) in question answering communities, and accordingly rank candidate answers based on similarity of interest between answers and questions.Experimental results show that the method can effectively excavation user interest and improve the accuracy of answer selection.
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