基于词贡献度的垃圾短信分类方法

A spam short message classification method based on word contribution

针对垃圾短信分类问题,提出了一种以词贡献度为基础的分类方法。该方法引入词贡献度的概念表达词在不同短信分类中的权重差别,通过构建词贡献度——分类矩阵和计算矩阵行均方差来实现降维,以词贡献度为基础计算短信隶属于短信分类的隶属度,并通过比较隶属度密度的方法解决分类冲突问题。实验结果表明,该方法在分类效果和实时性方面优于其他常用垃圾短信分类方法。

A classification method based on word contribution was proposed to classify spam short messages. The con- cept of word contribution was introduced for representing weight difference of a word in different categories, the word contribution-classification matrix was constructed, then the mean square deviation of each row in the matrix was compu- ted to reduce dimensionalities. To determine the classification a short message belongs to, short message-category mem- bership degrees were calculated based on word contribution. Furthermore if category candidates were more than one, the classification conflict problem could be resolved by comparing the densities of short message-category membership de- gree. The experimental results showed that the proposed method was superior to other classification methods in the clas- sification result and real-time.