A Novel Approach for Clustering of Chinese Text Based on Concept Hierarchy

摘要：

After analyzing the disadvantages of traditional text clustering method based on keywords set, a novel approach for clustering of Chinese text based on concept hierarchy is presented. It introduces a Chinese topic classify dictionary as background knowledge to clustering of Chinese text It adopts a hierarchical coding system which reflects concept relevance among different words and uses Vector Space Model based on concept hierarchy to represent Chinese text. The experimental results show this approach is more effective than traditional text clustering method based on keywords set.

关键词： Text Clustering Vector Space Model Chinese topic classify dictionary

作者: ZHAO PENG GENG HUAN-TONG CAI QING-SHENG

作者单位: Department of Computer Science and Technology, University of Science and Technology of China, Hefei Department of Computer Science and Technology, University of Science and Technology of China, Hefei

会议类型: 国际会议

会议名称: Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

会议地点: 北京

会议语种:英文

页码: 607-611

在线出版日期: 2006-07-17（万方平台首次上网日期，不代表论文的发表时间）