Inductive Databases and Knowledge Scouts
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The development of very large databases and WWW has created extraordinary opportunities for monitoring, analyzing and predicting economical, ecological, demographic, and other processes in the world. Our current technologies for data mining are, however, insufficient for such tasks. This talk will describe an ongoing research in the GMU MLI Laboratory on the development of “inductive databases and knowledge scouts” that represent a new approach to the problem of semi-automatically deriving user-oriented knowledge from databases. If time permits, a demo will be presented that illustrates the methodology natural induction that is at the heart of this research.
Ryszard S. Michalski is Planning Research Corporation Chaired Professor of Computational Sciences, and Director of the Machine Learning and Inference Laboratory at George Mason University. He is also Fellow of AAAI, and a Foreign Member of the Polish Academy of Sciences. Dr. Michalski is viewed as a co-founder of the field of machine learning and has initiated a number of research directions, such as constructive induction, conceptual clustering, variable-precision logic (with Patrick Winston, MIT), human plausible reasoning (with Alan Collins, BBN), multistrategy learning, the LEM model of non-Darwinian evolutionary computation, and most recently inductive databases and knowledge scouts. He has authored, co-authored and co-edited 14 books/proceedings, and over 350 papers in the areas of his interest.