DocumentCode :
3287087
Title :
Research on keywords Extraction of Chinese documents based on TEXT-NET
Author :
Liu, Gang ; Zhai, Zhouwei
Author_Institution :
Sch. of Electron. & Eng., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2011
fDate :
15-17 April 2011
Firstpage :
6074
Lastpage :
6077
Abstract :
A keywords Extraction algorithm of Chinese documents based on TEXT-NET is proposed. By using Semantic similarity computation of Howmet theory, a text is mapped a TEXT-NET, and then combined with complex network theory and statistical methods to extract keywords. Experimental results show that the recall and precision rate has increased compared with small-world model method and statistical methods, and this method is more flexible because it is independent of fields.
Keywords :
complex networks; natural language processing; statistical analysis; text analysis; Chinese documents; Howmet theory; TEXT-NET; complex network theory; keywords extraction algorithm; semantic similarity computation; small-world model method; statistical methods; Analytical models; Complex networks; Computational modeling; Computers; Feature extraction; Frequency measurement; Semantics; average path length; chinese information processing; clustering coefficient; complex network; keywords extraction; semantic similarity; text network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Information and Control Engineering (ICEICE), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-8036-4
Type :
conf
DOI :
10.1109/ICEICE.2011.5777961
Filename :
5777961
Link To Document :
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