摘要
文本分类是信息处理的重要研究方向,现在应用较多的是基于统计计算的分类方法。介绍了利用模糊认知图的文本分类推理理论与算法,该方法是基于数值推理的,实现将统计与规则融合推理,灵活性较大,不需要语料的多次训练,适合于训练不充分和新主题的文本分类和多类分类,并具有一定的鲁棒性。
Text categorization is an important direction of information processing,and now the categorization based on statistics computation is widely applied.This paper introduces the reference theory and algorithm of text categorization by using fuzzy cognitive map,which is based on value inference and can be able to infer by combing rule and statistics.This method is flexible and robust,and we do not need train the corpus time after time,it suits for the text categorization insufficiency train and new subject and multi-classification.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第12期155-158,共4页
Computer Engineering and Applications
基金
天津市自然科学基金(the Natural Science Foundation of Tianjin of China under Grant No.033610811)
天津市科技攻关重点项目(No.04310731R)
关键词
文本分类
模糊认知图
推理算法
text categorization
fuzzy cognitive map
reference algorithm
