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