Chinese Text Clustering Method Based on Semantics and Special Domain

Author

Jianquan, Dong ; Jinchao, Zhang

Author_Institution

Sch. of Comput. Eng. & Sci., Shanghai Univ., Shanghai, China

fYear

2009

fDate

7-8 Nov. 2009

Firstpage

195

Lastpage

199

Abstract

In view of ignoring semantic relationship between words, high dimensionality of data and computational complexity when current text clustering algorithms deal with Chinese texts. This paper presents a new method to cluster Chinese texts based on semantics in a specific field-TCBS (Text Clustering Based on Semantics) algorithm. The algorithm is based on the agglomerative hierarchical clustering algorithm, it expresses Chinese texts with the characteristic words and sets relative threshold in order to improve the efficiency of clustering. Compared with the traditional algorithms, the experimental results show that TCBS has effectively enhanced the quality of the clustering.

Keywords

natural language processing; pattern clustering; text analysis; Chinese text clustering; agglomerative hierarchical clustering algorithm; computational complexity; data dimensionality; word semantic relationship; Algorithm design and analysis; Clustering algorithms; Clustering methods; Computational complexity; Data engineering; Data mining; Information systems; Machine learning; Sun; Text processing; TCBS; Text clustering; characteristic words; semantic; similarity;

fLanguage

English

Publisher

ieee

Conference_Titel

Web Information Systems and Mining, 2009. WISM 2009. International Conference on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3817-4

Type

conf

DOI

10.1109/WISM.2009.47

Filename

5369484