关键词: 常见问题集, 问句相似度, 语义相似度, 向量空间模型

Abstract: FAQ system is a QA retrieval system to find the question sentence that matched with the user question sentence to the set of "question-answer" pairs, and return its corresponding answer to user. Its key question is that questions asked by user and questions in the FAQ carry on similarity computation, discover the closest question in the FAQ and return the question answer stored in advance. This paper presented a question similarity computation approach based on splited vector space model and semantic concept according to the common question characteristic research. The main thought is that splitting a question vector, extracting the main three components—question point, keyword and interrogative, expressing three components, then computing semantic similarity to every component based on “Synonym Word Dictionary” and obtaining two semantic similarity of questions by the linear weighting. The experiment indicates that precision of question match can be improved compared to traditional question similarity computation based on TF-IDF computation of vector space model.

Key words: FAQ, Sentence Similarity, Semantic Similarity, Vector Space Model