Method for Feature Word Weight Calculating

摘要：

Automatic text categorization has been one of the hotspots in the information processing field.To aim at the important impact of feature weight calculating on text classification accuracy, first, the relationship between text representation model and feature weight calculating is studied.and the existed methods of feature weight calculating are analyzed, then the common idea of feature weighting for vector space model (VSM) summarized.Second, the feature weighting thoughts for class space model (CSM) are gived, and on the basis of some existed methods, a number of feature weight calculating methods for CSM are proposed. Experimental results show that the proposed methods are effective in improving classification performance.After analyzing the experimental results, this paper points out that the appearance and the disappearance of feature words together to consider will lower the classification accuracy,so the favorable factors of a class should be highlighted, and the negative side should be ignored or minused.

关键词： tezt classification feature weight vector space model (VSM) class space model (CSM) category weight

作者: Yanling Li Jing Yuan Xia Ye

作者单位: College of Automation,Northwestern Polytechnic University;Xian Research Institute of Hi-Technology Xian Research Institute of Hi-Technology Xian,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 309-312

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）