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Spam messages classification algorithm based on BP and isomap

机译:基于BP和isomap的垃圾邮件分类算法

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摘要

In this paper, a classification algorithm for spam messages by using the neural network is proposed. First, the spam messages are pretreated, including word separation, feature word extraction, representation with feature word, and formation of text matrix. Then, the dimensionality of the text matrix is reduced by using isomap algorithm. Finally, the classification is achieved by the BP neural network. According to the experimental results, the algorithm gives good classification results.
机译:提出了一种基于神经网络的垃圾邮件分类算法。首先,对垃圾邮件进行预处理,包括分词,特征词提取,特征词表示以及文本矩阵的形成。然后,通过使用isomap算法降低文本矩阵的维数。最后,通过BP神经网络实现分类。根据实验结果,该算法给出了很好的分类结果。

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