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Title: Email Mining: Emerging Techniques for Email Management
Author(s): I. Katakis, G. Tsoumakas, I. Vlahavas.
Availability: Click here to download the PDF (Acrobat Reader) file.
Keywords: email, e-mail, mining, text, data streams, email classification, email clustering, automatic answering, spam filtering, text mi ning.
Appeared in: Web Data Management Practices: Emerging Techniques and Technologies, Athena Vakali, George Pallis (Ed.), Idea Group Publishing, pp. 219-240, 2006.
Abstract: Email has met tremendous popularity over the past few years. People are sending and receiving many messages per day, communicating with partners and friends, or exchanging files and information. Unfortunately, the phenomenon of email overload has grown over the past years becoming a personal headache for users and a financial issue for companies. In this chapter, we will discuss how disciplines like Machine Learning and Data Mining can contribute to the solution of the problem by constructing intelligent techniques which automate email managing tasks and what advantages they hold over other conventional solutions. We will also discuss the particularity of email data and what special treatment it requires. Some interesting email mining applications like mail categorization, summarization, automatic answering and spam filtering will be also presented.
See also : Book Page at the IDEA Group Web Site

        This paper has been cited by the following:

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