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Bayesian spam filtering for Vietnamese emails

机译:贝叶斯垃圾邮件过滤越南电子邮件

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摘要

Spam filtering is seen as the considerable concern to the researchers, and there are some techniques and email filtering systems are implemented. They are, however, not so effective for Vietnamese language. Although methods for filtering English spam email can be still used in Vietnamese language, but Vietnamese has its own particular characteristic. The biggest difference is a signified word in Vietnamese usually a compound. When a compound used in spam email is separated into single words, it becomes words that are usually used in both spam and ham emails. This leads to the difficulty for the system to filter spam emails. The objective of this paper is to present a new model using the application of Naïve Bayesian algorithms to analyze the segmentation of Vietnamese language. The process of demonstration and evaluation of this model shows the feasibility of this technique in filtering Vietnamese email.
机译:垃圾邮件过滤被研究人员视为相当关注的问题,并且有一些技术和电子邮件过滤系统得以实现。但是,对于越南语而言,它们并不那么有效。尽管过滤英语垃圾邮件的方法仍然可以使用越南语,但是越南语具有其自身的特点。最大的区别是越南语中的一个带有标志的词,通常是一个复合词。将垃圾邮件中使用的化合物分隔成单个单词时,它将成为垃圾邮件和非垃圾邮件中通常使用的单词。这导致系统难以过滤垃圾邮件。本文的目的是使用朴素贝叶斯算法来分析越南语的分割情况,提出一种新的模型。该模型的演示和评估过程显示了该技术在过滤越南电子邮件中的可行性。

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