A Kind of Text Classification Method Based on Fuzzy Vector Space Model and Neural Networks
A kind of text classification method based on fuzzy vector space model and neural networks is proposed in the paper according to the problems that a text can be belongs to many types during the text classification.Fuzzy theory is adopted in the method to look the occurring position of feature items in text on as the important degree (membership) reflecting text subject,and fully considered the position information while the features are extracted,thus the fuzzy feature vectors are constructed,as a result,the text classification is close to the manual classification method.The established networks are constituted of input layer,hidden layer and output layer,the input layer completes the inputs of classification samples,hidden layer extract(s) the implicit pattern features of input samples,the output layer is used to output the classification results.Finally the effectiveness of this method is proved by some documents of Wan Fang data in experimental section.
Text classification fuzzy vector space neural networks fuzzy feature vector feature extracted membership
JunHui PAN Hui LI
Department of Computer and Information Technology NorthEast Petroleum University Daqing,Heilongjiang,China
国际会议
杭州
英文
1960-1962
2013-03-22（万方平台首次上网日期，不代表论文的发表时间）