Title: Sequential data mining
Abstract: Data representing DNA, proteins, literature, weather, and the stock market all share one common characteristic: their data are sequential. Sequence data present some of the most challenging problems for machine learning and data mining methods. In this talk, Professor Brian King will present a generalized, probabilistic framework for modeling sequential data. He will show how he and his students have adapted this model for classification and prediction tasks, reporting results from recent studies.