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Mining categories for emails via clustering and pattern discovery

机译:通过集群和模式发现来挖掘电子邮件的类别

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The continuous exchange of information by means of the popular email service has raised the problem of managing the huge amounts of messages received from users in an effective and efficient way. We deal with the problem of email classification by conceiving suitable strategies for: (1) organizing messages into homogeneous groups, (2) redirecting further incoming messages according to an initial organization, and (3) building reliable descriptions of the message groups discovered. We propose a unified framework for handling and classifying email messages. In our framework, messages sharing similar features are clustered in a folder organization. Clustering and pattern discovery techniques for mining structured and unstructured information from email messages are the basis of an overall process of folder creation/maintenance and email redirection. Pattern discovery is also exploited for generating suitable cluster descriptions that play a leading role in cluster updating. Experimental evaluation performed on several personal mailboxes shows the effectiveness of our approach.
机译:通过流行的电子邮件服务的信息的连续交换提出了以有效和高效的方式管理从用户接收的大量消息的问题。我们通过构思以下合适的策略来处理电子邮件分类的问题:(1)将消息组织为同类组;(2)根据初始组织将其他传入消息重定向;(3)对发现的消息组进行可靠的描述。我们提出了用于处理和分类电子邮件的统一框架。在我们的框架中,共享相似功能的邮件聚集在一个文件夹组织中。用于从电子邮件中挖掘结构化和非结构化信息的群集和模式发现技术是文件夹创建/维护和电子邮件重定向的整个过程的基础。模式发现还被用于生成合适的集群描述,该集群描述在集群更新中起着主导作用。在几个个人邮箱上进行的实验评估表明了我们方法的有效性。

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