An Automatic Keyword Extraction of Chinese Document Algorithm Based on Complex Network Features
ZHAO Peng1,2, CAI QingSheng1,WANG QingYi1, GENG HuanTong1
1.Department of Computer Science and Technology, University of Science and Technology of China, Hefei 230027 2.Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Anhui University, Hefei 230039
Abstract Automatic keyword extraction is one of the most important techniques in natural language processing. In this paper, features of complex networks composed of Chinese are studied. A novel automatic keyword extraction algorithm for Chinese document is proposed which is based on the features of the complex networks according to the small world structure in language networks and the theoretical achievements in complex networks. It extracts keyword based on the feature values of the word nodes in a documental language network. Experimental results show the proposed algorithm obtains higher average precision compared with the keyword extraction algorithm based on TFIDF.
ZHAO Peng,CAI QingSheng,WANG QingYi等. An Automatic Keyword Extraction of Chinese Document Algorithm Based on Complex Network Features[J]. , 2007, 20(6): 827-831.
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2007, Vol. 20 
