Information Technology Laboratory

Abstract
Recent Developments in Data Mining

Systems for extracting interesting structure from databases, Especially large data stores, are becoming a necessity. The existing data access model is clearly hitting its limits. Data Mining methods provide away to address some of these problems. These methods have their origins in statistics, databases, pattern recognition, learning, visualization, and parallel computing. I'll outline some recent advances towards scaling mining algorithms to large databases, and cover the research challenges and opportunities posed by the problem of extracting models from massive data sets. The talk will particularly focus on the decomposition of classification and clustering algorithms so that they work effectively with a database system backend.


Biography
Usama Fayyad is a Senior Researcher at (Microsoft Research). His research interests include scaling data mining algorithms to large databases, learning algorithms, and statistical pattern recognition, especially classification and clustering. He is Editor-in-Chief of the journal, Data Mining and Knowledge Discovery.