Synopsis
This book provides the reader with a complete view of the different tools used in the analysis of data for scientific discovery. The book offers both an overview of the state-of-the-art, and lists areas and open issues for future research and development.
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Scientific Data Mining and Knowledge Di (eng)
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Scientific Data Mining and Knowledge Discovery: Principles and Foundations
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Scientific Data Mining and Knowledge Discovery: Principles and Foundations
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Scientific Data Mining and Knowledge Discovery
Edité par
Springer Berlin Heidelberg, Springer Berlin Heidelberg Nov 2014, 2014
ISBN 10 : 3642426247
ISBN 13 : 9783642426247
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 412 pp. Englisch. N° de réf. du vendeur 9783642426247
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Scientific Data Mining and Knowledge Discovery
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Springer Berlin Heidelberg, 2014
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ISBN 13 : 9783642426247
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Scientific Data Mining and Knowledge Discovery | Principles and Foundations
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Taschenbuch. Etat : Neu. Scientific Data Mining and Knowledge Discovery | Principles and Foundations | Mohamed Medhat Gaber | Taschenbuch | x | Englisch | 2014 | Springer Vieweg | EAN 9783642426247 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 104913848
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Scientific Data Mining and Knowledge Discovery
Edité par
Springer Berlin Heidelberg, Springer Berlin Heidelberg Nov 2014, 2014
ISBN 10 : 3642426247
ISBN 13 : 9783642426247
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 412 pp. Englisch. N° de réf. du vendeur 9783642426247
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Scientific Data Mining and Knowledge Discovery : Principles and Foundations
Edité par
Springer Berlin Heidelberg, 2014
ISBN 10 : 3642426247
ISBN 13 : 9783642426247
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N° de réf. du vendeur 9783642426247
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Scientific Data Mining and Knowledge Discovery: Principles and Foundations
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Springer, 2014
ISBN 10 : 3642426247
ISBN 13 : 9783642426247
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