Wednesday, August 10, 2011

Blog: Researcher Teaches Computers to Detect Spam More Accurately

Researcher Teaches Computers to Detect Spam More Accurately
IDG News Service (08/10/11) Nicolas Zeitler

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 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 emails are spam and which are not, which is very inefficient, according to Balcan. Active learning enables the computer to analyze huge collections of unlabeled emails 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.

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