Finding topics in email using formal concept analysis and fuzzy membership functions

From National Research Council Canada

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DOIResolve DOI: https://doi.org/10.1007/978-3-540-68825-9_11
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Name affiliation
  1. National Research Council Canada. NRC Institute for Information Technology
FormatText
TypeBook chapter
Proceedings titleAdvances in Artificial Intelligence : 21st Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2008 Windsor, Canada, May 28-30, 2008 Proceedings
Series titleLecture Notes In Computer Science; Volume 5032
ConferenceThe 21st Canadian Conference on Artificial Intelligence (CAI 2008), May 28-30, 2008, Windsor, Ontario, Canada
ISSN0302-9743
Pages108–113; # of pages: 6
Abstract
In this paper, we present a method to identify topics in email messages. The formal concept analysis is adopted as a semantic analysis method to group emails containing the same keywords to concepts. The fuzzy membership functions are used to rank the concepts based on the features of the emails, such as the senders, recipients, time span, and frequency of emails in the concepts. The highly ranked concepts are then identified as email topics. Experimental results on the Enron email dataset illustrate the effectiveness of the method.
Publication date
PublisherSpringer Berlin Heidelberg
LanguageEnglish
Peer reviewedYes
NRC number50327
NPARC number5765135
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Record identifierc21739fa-1e09-4131-8286-d905874a1c19
Record created2009-03-29
Record modified2019-01-31
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