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.
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