DocumentCode
423345
Title
An algorithm for conceptual clustering of Chinese text
Author
Cai, Zhi ; Geng, Wan-Tong ; Zhao, Xin ; Cai, Qing-Sheng
Author_Institution
Dept. of Comput. Sci. & Technol., Univ. of Sci. & Technol. of China, China
Volume
5
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
3035
Abstract
In this paper, an algorithm for conceptual clustering of Chinese text is presented. Authors adopt ontology - Hownet, use VSM (vector space model) to represent document. Then, the authors cluster the document by a partitioned algorithm. The test results show this algorithm is more efficient than the traditional text clustering method based on the keywords set.
Keywords
ontologies (artificial intelligence); pattern clustering; text analysis; Chinese text clustering; Hownet; conceptual clustering; document clustering; ontology; vector space model; Clustering algorithms; Clustering methods; Computer aided instruction; Documentation; Ontologies; Partitioning algorithms; Space technology; Taxonomy; Text mining; Tree data structures;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1378553
Filename
1378553
Link To Document