摘要
TFIDF是文档特征权重表示常用方法.该方法简单易行,但忽略了特征词在各个类别中的分布情况,不能真正地反映特征词对区分每个类的贡献.针对这个不足,本文提出了BOR-TFIDF,来重新调整每个特征词对各个类别的区分度,即修正各个特征词的权重,并用分类器来验证其有效性.该方法优于原来的TFIDF算法,实验表明了改进的策略是可行的.
TFIDF is a kind of common methods used to measure the terms in a document. The method is easy but ig- nores the distribution of the feature in each class. So, it can not really reflect each feature＇ s contribution to each class. Aiming at this shortage, we put forward the BOR-TFIDF and use it to readjust each feature＇ s differentiation to each class, i.e. , modifies each feature＇ s weight. Then the classifier is used to check its validaty. The method is better than traditional TFIDF and proves that the BOR-TFIDF method is feasible.
出处
《南京师范大学学报（工程技术版）》
CAS
2008年第4期95-98,149,共5页
Journal of Nanjing Normal University(Engineering and Technology Edition)
基金
教育部留学回国人员启动基金
中科院软件所开放课题基金(SYSKF0701)
福州大学科技发展基金(2005-XQ-13)
福建省教育厅基金(JB06023)资助项目
