Research on the categorization accuracy of different similarity measures on Chinese texts

摘要：

This paper works on the most intensively studied algorithm k Nearest Neighbor algorithm. The purpose is to investigate the performance of different similarity measures in the kNN on Chinese texts. The two measures that we focus on are cosine value and JensenShannon Divergence. We use both the corpus collected from the Sogou, whose data extracts from the website of Sohu.com, and datasets that we have processed from real word. The results of our experiment indicate that difference of similarity metrics significantly affects the categorization accuracy.

关键词： Chinesetextcategorization Similarity SougouCorpus KNNalgorithm

作者: Xiangdong LI Hangyu LIU Han JIA Li HUANG

作者单位: The School of Information Management,Wuhan University, Wuhan 430072, China Wuhan University Library, Wuhan University, Wuhan 430072, China

会议类型: 国际会议

会议名称: 2011 International Conference on Business Management and Electronic Information(2011商业管理与电子信息国际学术会议 BMEI2011)

会议地点: 广州

会议语种:英文

页码: 1-4

在线出版日期: 2011-05-13（万方平台首次上网日期，不代表论文的发表时间）