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million Enron emails and the use of a variety of techniques from the field of Corpus Linguistics for reducing the number of false alarms produced by naive keyword filtering systems, and discuss the results in detail. We also give due consideration to the danger of missing messages that should have been prevented from
of the classifier. Our experimental results shows that these measures can improve the classifier's performances, for keywords change too rapidly in emails while address groups are much steadier.
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