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Researcher Teaches Computers to Detect Spam More Accurately

By IDG News Service

August 12, 2011

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Georgia Tech researcher Nina Balcan recently received a Microsoft Research Faculty Fellowship for her work in developing machine learning methods that can be used to create personalized automatic programs for deciding whether an email message is spam or not.

Balcan's research also can be used to solve other data-mining problems. Using supervised learning, the user teaches the computer by submitting information on which email messages are spam and which are not, which is very inefficient, according to Balcan.

Active learning enables the computer to analyze huge collections of unlabeled email messages to generate only a few questions for the user. Active learning could potentially deliver better results than supervised learning, Balcan says. However, active learning methods are highly sensitive to noise, making this potentially difficult to achieve.

Balcan plans to develop an understanding of when, why, and how different kinds of learning protocols help. "My research connects machine learning, game theory, economics, and optimization," she says.

From IDG News Service
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