KNN Text Categorization Algorithm Based On LSA Reduce Dimensionality

摘要：

Aimed at .the problem of document automatic classification, an improved KNN algorithm is proposed based on LSA reduced dimensionality. It advances the KNN algorithms efficiency and classifiers precision by using LSA to reduce dimensionality of text feature matrix. The experiment result shows that the improved KNN algorithm has good performance.

关键词： latent semantic analysis KNN text categorization reduced dimensionality

作者: Liangjun Li Yuanyuan Che Hongliang Zhang Tienan Li Ming Yang

作者单位: Computing Center of Anshan Normal University Anshan,Liaoning China 114003 School of Computer Science and Automatic Control Hebei United University Tangshan,Hebei,China 063000

会议类型: 国际会议

会议名称: 2011 6th Joint International Information Technology and Artificial Intelligence Conference(2011年第六届IEEE联合国际信息技术与人工智能会议 IEEE ITAIC 2011)

会议地点: 重庆

会议语种:英文

页码: 575-578

在线出版日期: 2011-08-20（万方平台首次上网日期，不代表论文的发表时间）