BibSonomyburst/user/cschenk/emailBibSonomy RSS feed for /user/cschenk/email2012-02-16T06:44:35+01:00http://www.bibsonomy.org/bibtex/243d2c72e40212957f3d6ed66a4a104b3/cschenkcschenk2008-06-30T16:14:54+02:00article blacklists email ip ix read:2008 spam <span class="authorEditorList"><a href="/author/Rossow">Christian Rossow</a>, <a href="/author/Dietrich">Christian Dietrich</a>, and <a href="/author/Pohlmann">Norbert Pohlmann</a> </span><em>iX</em> (<em>January 2008</em>)Mon Jun 30 16:14:54 CEST 2008iXJanuar56-61Blockwerk. IP-Blacklists sinnvoll kombinieren12008article blacklists email ip ix read:2008 spam http://www.bibsonomy.org/bibtex/22e725bdb785392dfa38fe4ff68fd965f/cschenkcschenk2008-06-30T16:03:06+02:00adressen article email ix newsletter read:2008 spam <span class="authorEditorList"><a href="/author/Ungerer">Bert Ungerer</a> </span><em>iX</em> (<em>January 2008</em>)Mon Jun 30 16:03:06 CEST 2008iXJanuar48-54Vorsorgemaßnahmen. Korrekter Umgang mit E-Mail-Adressen12008adressen article email ix newsletter read:2008 spam http://www.bibsonomy.org/bibtex/2c66fa858b58398f469558c5d85cf8a7a/cschenkcschenk2008-06-21T18:52:26+02:00algorithms automatic bayes benchmark categorization classification email enron folders information ir paper read:2008 retrieval sri svm winnow <span class="authorEditorList"><a href="/author/Bekkerman">R. Bekkerman</a>, <a href="/author/McCallum">A. McCallum</a>, and <a href="/author/Huang">G. Huang</a> </span><em>Center for Intelligent Information Retrieval, Technical Report IR</em> (<em>2004</em>)Sat Jun 21 18:52:26 CEST 2008Center for Intelligent Information Retrieval, Technical Report IRAutomatic Categorization of Email into Folders: Benchmark Experiments on Enron and SRI Corpora4182004algorithms automatic bayes benchmark categorization classification email enron folders information ir paper read:2008 retrieval sri svm winnow Office workers everywhere are drowning in email—not only spam, but also large quantities of legitimate email to be read and organized for browsing. Although there have been extensive investigations of automatic document categorization, email gives rise to a number of unique challenges, and there has been relatively little study of classifying email into folders. This paper presents an extensive benchmark study of email foldering using two large corpora of real-world email messages and foldering schemes: one from former Enron employees, another from participants in an SRI research pro ject. We discuss the challenges that arise from differences between email foldering and traditional document classification. We show experimental results from an array of automated classification methods and evaluation methodologies, including a new evaluation method of foldering results based on the email timeline, and including enhancements to the exponential gradient method Winnow, providing top-tier accuracy with a fraction the training time of alternative methods. We also establish that classification accuracy in many cases is relatively low, confirming the challenges of email data, and pointing toward email foldering as an important area for further research.