基于概念向量空间模型的电子邮件分类

提出了一个基于概念向量空间模型的电子邮件分类方法。在提取电子邮件特征向量时，以WordNet语言本体库为基础，以同义词集合概念代替词条，同时考虑同义词集合间的上下位关系，从而建立电子邮件的概念向量空间模型作为电子邮件的特征向量。使用TF*IWF*IWF方法对概念向量进行权值修正，最后通过简单向量距离分类方法来确定电子邮件的类别。实验结果表明，当训练集合数目有限时，该方法能够有效提高电子邮件的分类准确率。

E-mail classification based on concept vector space model

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.