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The Enron corpus: A new dataset for email classification research. (English) Zbl 1132.68562
Boulicaut, J.-F. (ed.) et al., Machine learning: ECML 2004. 15th European conference on machine learning, Pisa, Italy, September 20–24, 2004, Proceedings. Berlin: Springer (ISBN 978-3-540-23105-9/pbk). Lecture Notes in Computer Science 3201. Lecture Notes in Artificial Intelligence, 217-226 (2004).
Summary: 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.
For the entire collection see [Zbl 1131.68005].

MSC:
68T05 Learning and adaptive systems in artificial intelligence
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