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Knowledge Discovery from Evolving Data

Knowledge Discovery from Evolving Data

This video was recorded at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Antwerp 2008. Data mining has traditionally concentrated on the analysis of a static world, in which data instances are collected, stored and analyzed to derive models and take decisions according to them. More recent research on stream mining has put forward the need to deal with data that cannot be collected and stored statically but must be analyzed on the fly. At the same time, the need to store, maintain, query and update models derived from the data has been recognized and advocated [LT08]. However, these are only two aspects of the dynamic world that must be analyzed with data mining: The world is changing and so do the accumulating data and,... Show More
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