Scientific Data Mining and Knowledge Discovery: Principles and Foundations

Author:   Mohamed Medhat Gaber
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   2010 ed.
ISBN:  

9783642426247


Pages:   400
Publication Date:   20 November 2014
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Scientific Data Mining and Knowledge Discovery: Principles and Foundations


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Overview

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.

Full Product Details

Author:   Mohamed Medhat Gaber
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   2010 ed.
Dimensions:   Width: 15.50cm , Height: 2.10cm , Length: 23.50cm
Weight:   0.629kg
ISBN:  

9783642426247


ISBN 10:   3642426247
Pages:   400
Publication Date:   20 November 2014
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Background.- Machine Learning.- Statistical Inference.- The Philosophy of Science and its relation to Machine Learning.- Concept Formation in Scientific Knowledge Discovery from a Constructivist View.- Knowledge Representation and Ontologies.- Computational Science.- Spatial Techniques.- Computational Chemistry.- String Mining in Bioinformatics.- Data Mining and Knowledge Discovery.- Knowledge Discovery and Reasoning in Geospatial Applications.- Data Mining and Discovery of Chemical Knowledge.- Data Mining and Discovery of Astronomical Knowledge.- Future Trends.- On-board Data Mining.- Data Streams: An Overview and Scientific Applications.

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