摘要
文章研究了基于向量空间模型的文本分类中特征词权重算法,综合考虑特征词在文本中出现的位置信息,提出一种改进算法并给出实验结果。
This article mainly researches the algorithm of feature term weighting on text categorization based on vector space model considering the impression of the feature term position. An improved algorithm of feature term weighting is given. The comparison of experimental results proves that the improved approaches can improve the precision of text categorization.
出处
《安徽水利水电职业技术学院学报》
2008年第1期64-66,共3页
Journal of Anhui Technical College of Water Resources and Hydroelectric Power
基金
安徽省教育厅自然科学研究项目(NO.KJ2008B120)
关键词
文本分类
特征权重
向量空间模型
位置权重
text categorization
feature weighting
vector space model
position weighting
