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Scientific Data Mining and Knowledge Discovery - Principles and Foundations (Paperback, 2010 ed.)
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Scientific Data Mining and Knowledge Discovery - Principles and Foundations (Paperback, 2010 ed.)
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Mohamed Medhat Gaber "It is not my aim to surprise or shock you -
but the simplest way I can summarise is to say that there are now
in the world machines that think, that learn and that create.
Moreover, their ability to do these things is going to increase
rapidly until - in a visible future - the range of problems they
can handle will be coextensive with the range to which the human
mind has been applied" by Herbert A. Simon (1916-2001) 1Overview
This book suits both graduate students and researchers with a focus
on discovering knowledge from scienti c data. The use of
computational power for data analysis and knowledge discovery in
scienti c disciplines has found its roots with the re- lution of
high-performance computing systems. Computational science in
physics, chemistry, and biology represents the rst step towards
automation of data analysis tasks. The rational behind the
developmentof computationalscience in different - eas was
automating mathematical operations performed in those areas. There
was no attention paid to the scienti c discovery process. Automated
Scienti c Disc- ery (ASD) [1-3] represents the second natural step.
ASD attempted to automate the process of theory discovery supported
by studies in philosophy of science and cognitive sciences.
Although early research articles have shown great successes, the
area has not evolved due to many reasons. The most important reason
was the lack of interaction between scientists and the automating
systems.
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