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
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;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1378553
