Adding Lexical Chain to Keyphrase Extraction

Key phrase extraction is widely used in information retrieval, automatic summarizing, text clustering, etc. KEA is a traditional and classical algorithm. But it mainly uses the statistical information and ignores the semantic information. In our paper, we propose a method which combine semantic information with KEA by constructing lexical chain that based on Reget´s thesaurus. In this method, we use the semantic similarity between terms to construct lexical chain, and then the length of the chain will be used as a feature to build the extraction model. The experiment results attest that the performance of our system has an obvious improvement compare with the KEA and Nguyen and Kan´s method.