本文主要研究了基于内容的垃圾短信过滤，它可以看成是一个不规则短文本的分类问题。
In this thesis, the main research is content-based junk short messages filtering which can be treated as irregular short text classification problem.
因此垃圾短信过滤是当今学术界研究的一大热点也是难点，但它同时也是广大手机用户的迫切需求。
The research on the junk short message filtering becoming hot since it is the urgent requirement of the mobile phone users.
因此，许多中国人开始抱怨这些垃圾短信，他们希望过滤掉这些信息，不向他们的手机发送这些垃圾短信。
As a result, many people in China have begun to complain about these rubbish messages, and would prefer that these messages were filtered out and not send to their mobile phones.
为此，他们需要一种方法来通过网关分类短信，然后过滤掉那些垃圾短信。
To do this, they needed a way to classify short messages received through a gateway and then filter out the rubbish or spam messages.
通过机器学习的方式，对垃圾短信进行判断，过滤。
And it USES the method of machine learning to judge and filter spam messages.
同垃圾短信管理器，您可以有效地过滤所有您接收短信。
With SMS Spam Manager you can effectively filter all your incoming SMS messages.
抽取电子邮件和手机短信的多种文本特征，分别在TREC07P电子邮件语料和真实中文手机短信语料上进行了垃圾信息过滤实验。
Through multiple text features extraction from email and short message service (SMS) document, some spam filtering experiments are run on TREC07P email corpus and real Chinese SMS corpus separately.
抽取电子邮件和手机短信的多种文本特征，分别在TREC07P电子邮件语料和真实中文手机短信语料上进行了垃圾信息过滤实验。
Through multiple text features extraction from email and short message service (SMS) document, some spam filtering experiments are run on TREC07P email corpus and real Chinese SMS corpus separately.
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