The Enron Corpus: A New Dataset for Email Classification Research

  • Bryan Klimt
  • Yiming Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3201)


Automated classification of email messages into user-specific folders and information extraction from chronologically ordered email streams have become interesting areas in text learning research. However, the lack of large benchmark collections has been an obstacle for studying the problems and evaluating the solutions. In this paper, we introduce the Enron corpus as a new test bed. We analyze its suitability with respect to email folder prediction, and provide the baseline results of a state-of-the-art classifier (Support Vector Machines) under various conditions, including the cases of using individual sections (From, To, Subject and body) alone as the input to the classifier, and using all the sections in combination with regression weights.


Ridge Regression Email Message Unstructured Text AAAI Spring Symposium Foldering Strategy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Bryan Klimt
    • 1
  • Yiming Yang
    • 1
  1. 1.Language Technologies InstituteCarnegie Mellon UniversityPittsburghUSA

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