Spam filtering based on statistics and token frequency modeling
    1.
    发明授权
    Spam filtering based on statistics and token frequency modeling 有权
    基于统计和令牌频率建模的垃圾邮件过滤

    公开(公告)号:US08364766B2

    公开(公告)日:2013-01-29

    申请号:US12328723

    申请日:2008-12-04

    IPC分类号: G06F15/16

    CPC分类号: H04L51/12 G06N7/005

    摘要: Embodiments are directed towards classifying messages as spam using a two phased approach. The first phase employs a statistical classifier to classify messages based on message content. The second phase targets specific message types to capture dynamic characteristics of the messages and identify spam messages using a token frequency based approach. A client component receives messages and sends them to the statistical classifier, which determines a probability that a message belongs to a particular type of class. The statistical classifier further provides other information about a message, including, a token list, and token thresholds. The message class, token list, and thresholds are provided to the second phase where a number of spam tokens in a given message for a given message class are determined. Based on the threshold, the client component then determines whether the message is spam or non-spam.

    摘要翻译: 实施例针对使用两阶段方法将消息分类为垃圾邮件。 第一阶段采用统计分类器根据消息内容分类消息。 第二阶段针对特定的消息类型来捕获消息的动态特征,并使用基于令牌频率的方法识别垃圾邮件。 客户端组件接收消息并将其发送到统计分类器,该分类器确定消息属于特定类型的类的概率。 统计分类器还提供关于消息的其他信息,包括令牌列表和令牌阈值。 消息类别,令牌列表和阈值被提供给第二阶段,其中给定消息类别的给定消息中的多个垃圾邮件令牌被确定。 基于阈值,客户端组件然后确定消息是垃圾邮件还是非垃圾邮件。

    SPAM FILTERING BASED ON STATISTICS AND TOKEN FREQUENCY MODELING
    2.
    发明申请
    SPAM FILTERING BASED ON STATISTICS AND TOKEN FREQUENCY MODELING 有权
    基于统计和TOKEN频率建模的垃圾邮件过滤

    公开(公告)号:US20100145900A1

    公开(公告)日:2010-06-10

    申请号:US12328723

    申请日:2008-12-04

    IPC分类号: G06N5/02 G06F15/16

    CPC分类号: H04L51/12 G06N7/005

    摘要: Embodiments are directed towards classifying messages as spam using a two phased approach. The first phase employs a statistical classifier to classify messages based on message content. The second phase targets specific message types to capture dynamic characteristics of the messages and identify spam messages using a token frequency based approach. A client component receives messages and sends them to the statistical classifier, which determines a probability that a message belongs to a particular type of class. The statistical classifier further provides other information about a message, including, a token list, and token thresholds. The message class, token list, and thresholds are provided to the second phase where a number of spam tokens in a given message for a given message class are determined. Based on the threshold, the client component then determines whether the message is spam or non-spam.

    摘要翻译: 实施例针对使用两阶段方法将消息分类为垃圾邮件。 第一阶段采用统计分类器根据消息内容分类消息。 第二阶段针对特定的消息类型来捕获消息的动态特征,并使用基于令牌频率的方法识别垃圾邮件。 客户端组件接收消息并将其发送到统计分类器,该分类器确定消息属于特定类型的类的概率。 统计分类器还提供关于消息的其他信息,包括令牌列表和令牌阈值。 消息类别,令牌列表和阈值被提供给第二阶段,其中给定消息类别的给定消息中的多个垃圾邮件令牌被确定。 基于阈值,客户端组件然后确定消息是垃圾邮件还是非垃圾邮件。