E-mail classification based on concept vector space model
基于概念向量空间模型的电子邮件分类

A new approach of e-mail classification based on the concept vector space model was proposed. In this approach, the eigenvector of the e-mail was extracted during training process by replacing terms with synonymy sets in WordNet and considering hypernymy-hyponymy relation between synonymy sets. Then, TF * IWF * IWF method was used to revise the weight of the concept vector. In the end, the type of e-mail was determined using the simple vector classification method. Compared with the term-based VSM approach, the results show that this approach can improve the accuracy of e-mail classification especially when the size of training set is small.