Enron Dataset Research: E-mail Relevance Classification
Date
2009-09-25
Authors
VanBuren, Victoria
Villarreal, David
McMillen, Thomas A.
Minnicks, Andrew L.
Journal Title
Journal ISSN
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Abstract
This paper discusses a probabilistic approach to address the problem of searching through large amount of data to find case-relevant documents. Using a valuable collection of data, e-mail communications from Enron, an actual corporation, we train a Bayes-based text classifier algorithm to identify e-mails known to be case-relevant and those known to be case-irrelevant.
Description
Keywords
enron dataset, e-mail Relevance, e-mail classification, Bayes classifier, electronic discovery, forensics, Computer Science
Citation
VanBuren, V., Villarreal, D., McMillen, T. A., & Minnick, A. L. (2009). Enron dataset research: E-mail relevance classification (Report No. TXSTATE-CS-TR-2009-12). Texas State University-San Marcos, Department of Computer Science.