Improvement of KEA Based on Lexical Chain
Keypbrases are very useful and significant for information retrieval,automatic summarizing,text clustering,etc.KEA is a traditional and classical algorithm in keyphrase automatic extraction.But it is mainly based on the statistical information without considering the semantic information.In this paper,We propose a method which combine semantic information with KEA by constructing lexical chain that based on Regets thesaiurus.In our method,the semantic similarity between terms is used to construct the lexical chain,and then we use the length of the chain as a feature to build the extraction modeL The experiment result shows that the performance of the system has a big improvement compare with the KEA.
keyphrases extraction KFA lexcial chain semantic similarity
Zefeng Li Xianghui Zhao Jin Yi Bin He
China Information Technology Security Evaluation Center, Beijing, China ;School of Information, Renm China Information Technology Security Evaluation Center, Beijing, China
国际会议
太原
英文
681-684
2012-12-08（万方平台首次上网日期，不代表论文的发表时间）