A Modified Approach to Keyword Eztraction Based on Word-similarity

摘要：

two keyword-extraction ways are usually used, one is simply using the information from exactly single word like word frequency and TF.JDF, the other is based on the relationship between words. The relationship is usually described as word similarity which derives from a corpus (WordNet, HowNet) or man-made thesaurus. With the information explosion nowdays, the words we using are growing and changing rapidly. A lot of new words are not specified in man-made corpus. This paper proposes a new method to build a word similarity thesaurus. Using the semantic information from the thesaurus, together with TF.IDF and words first occurrence, a keyword extraction algorithm is demonstrated, the results and analysis are also given.

关键词： keyword eztraction word similarity Jenson-Shannon divergence Naive Bayes

作者: Meng Wenchao Liu Lianchen Dai Ting

作者单位: National CIMS Engineering Research Center,Tsinghua University,Beijing,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 2203-2207

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）