中文摘要：

目前,很多在线学习的智能答疑方法是与FAQ库中的问题进行简单的关键词匹配,没有对问题进行语义理解,答疑的质量和效率较低,且FAQ库存在资源有限、不易更新等问题。基于这一点,提出了一种基于语义网分析的智能答疑方法,核心是利用中文分词技术提取关键词、关键词向量的语义扩展和相似度匹配,该方法考虑了关键词的语义,并优化了FAQ库的资源配置。对提出的智能答疑方法进行了实验验证,证明了该方法的可行性和优化性。

英文摘要：

Nowadays, many question-answering methods are achieved through keywords matching which lead to low quality arid efficien- cy due to lacking of semantic information of keywords, and the FAQ resources are limited and difficult to update. This paper proposes an intelligent question-answering method based on semantic web, the main idea is to the keywords through words segmentation tech- nology, the keyword vectors＂ semantic expansion and similarity matching. The method takes the keywords＂ semantic information into con- sideration, and also improves the quality of FAQ. The experiment implemented proves the validity of this method.