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Studying of Classifying Junk Messages Based on The Data Mining

机译:基于数据挖掘对垃圾邮件进行分类的研究

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Traditional SMS filters are basically text-based filtering. However, the filtering mechanisms have limitations: first, the keyword can easily be replaced by other symbols, which increase the difficulty of filtering; second, is garbage in the ongoing renovation of keywords, filtering mechanism of the high demands of intelligent learning, which is difficult to achieve. Send acts based on the analysis of the filter will be able to solve the above problems. Filters in the design of messages added to the idea of data mining, through classification analysis of the sent messages, thus can be extracted to identify the rules of spam text messages and can send messages to the new classification behavior.
机译:传统的SMS过滤器基本上是基于文本的过滤。但是,过滤机制具有限制:首先,关键字可以很容易地替换其他符号,这增加了过滤的难度;其次,在持续的翻新的关键词中是垃圾,过滤机制对智能学习的高要求,这很难实现。根据滤波器的分析发送行为将能够解决上述问题。通过对数据挖掘的思想的信息设计的过滤器,通过对发送消息的分类分析,可以提取以识别垃圾邮件文本消息的规则,并可以向新分类行为发送消息。

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