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中文摘要：
传统的问答系统（QA）只是直接返回问题的答案，而且没有用户交互特性，而基于社区的问答系统（CQA），含有大量的“问答对”可以利用。该文提出了一种基于LDA的匹配框架来解决相似问句的匹配问题，分别从问句的统计信息、语义信息和主题信息三个方面来计算问句相似度，综合得到整体相似度。实验是在Yahoo!Answers上抽取的真实标注数据集上进行，最终的实验结果表明，该文的方法达到了很好的性能。
英文摘要：
While the traditional question answering （QA） systems just find the answer to the question directly with- out user interaction, the community-based QA systems （CQA） employs large available QA archives. The paper pro- poses a new retrieval framework based ort LDA topics to find the similar questions according to the statistical, the semantic and the theme information. The experiments on the question-answer threads of the Yahoo! Answers show that our method achieved a good performance.
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