Semantic-based Keyword Extraction Algorithm for Chinese Text

In order to overcome the limitation of literal matching and lacking semantic concept of the traditional Keyword extraction algorithm,this paper presents a Semantic-based Keyword Extraction(SKE) algorithm for Chinese text.It uses semantic feature in the keyword extraction process and constructs word semantic similarity network and uses betweenness centrality density.Experimental results show that compared with the statistic based keyword extraction algorithm,the keywords SKE algorithm extracted are more reasonable and can represent more information of the document's topic,and the SKE algorithm has a better performance.