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Computational discovery of scientific knowledge

introduction, techniques, and applications in environmental and life sciences
  • 326 Pages
  • 3.21 MB
  • 2482 Downloads
  • English

Springer , Berlin, New York
Science -- Data processing -- Congresses, Discoveries in science -- Congresses, Electronic data processing -- Automation -- Congresses, Computational learning theory -- Congresses, Biology -- Research -- Data processing -- Congresses, Medicine -- Research -- Data processing -- Congresses, Computational Biology -- methods, Biotechnology -- methods, Models, Theoretical, Res
StatementSašo Džeroski, Ljupčo Todorovski (eds.).
GenreCongresses.
SeriesLNCS sublibrary, Lecture notes in computer science -- 4660. -- Lecture notes in artificial intelligence, State-of-the-art survey, Lecture notes in computer science -- 4660., Lecture notes in computer science, Lecture notes in computer science
ContributionsDžeroski, Sašo, 1968-, Todorovski, Ljupčo, 1969-, International Symposium on Computational Discovery of Communicable Knowledge (2001 : Stanford, Calif.)
Classifications
LC ClassificationsQ183.9 .C62 2007
The Physical Object
Paginationx, 326 p. :
ID Numbers
Open LibraryOL18020968M
ISBN 10354073919X
ISBN 139783540739197
LC Control Number2007931366

Computational Discovery of Scientific Knowledge: Introduction, Techniques, and Applications in Environmental and Life Sciences (Lecture Notes in Computer Science ()) [Dzeroski, Saso] on *FREE* shipping on qualifying offers.

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Computational Discovery of Scientific Knowledge: Introduction, Techniques, and Applications in Environmental and Life Sciences (Lecture Author: Saso Dzeroski. The 15 articles presented are partly inspired by the contributions of the International Symposium on Computational Discovery of Communicable Knowledge, held in Stanford, CA, USA in March More representative coverage of recent research in computational scientific discovery is achieved by a significant number of additional invited.

In contrast to mining scientific data, which focuses on building highly predictive models, computational scientific discovery puts a strong emphasis on discovering knowledge represented in formalisms used by scientists and engineers, such as numeric equations and reaction pathways.

Computational Discovery of Scientific Knowledge 5 temperature increases in one substance and a decrease in the other until they reach equilibrium.

The law also describes a precise numeric relationship between the initial Computational discovery of scientific knowledge book final temperatures.

The first statement is qualitative in Cited by: Get this from a library. Computational discovery of scientific knowledge: introduction, techniques, and applications in environmental and life sciences.

[Sašo Džeroski; Ljupčo Todorovski;] -- Advances in technology have enabled the collection of data from scientific observations, simulations, and experiments at an ever-increasing pace. For the scientist and engineer to benefit from these.

This chapter introduces the field of computational scientific discovery and provides a brief overview thereof. We first try to be more specific about what scientific discovery is and also place it in the broader context of the scientific by:   In this paper, we review AI research on computational discovery and its recent application to the discovery of new scientific knowledge.

We characterize five historical stages of the scientific discovery process, which we use as an organizational framework in describing applications.

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Description Computational discovery of scientific knowledge PDF

Computational Discovery of Scientific Knowledge: Introduction, Techniques, and Applications in Environmental and Life Sciences by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (Paperback, ) Be the Computational discovery of scientific knowledge book to write a review. a computational model of scientific insight that relied on analogical reasoning combined with spreading activiation retrieval.

And with Bernd Nordhausen, I constructed IDS, a system that integrated our previous work on taxonomy formation, discovery of qualitative laws. Thagard describes a detailed computational model of problem solving and discovery that provides a conceptually rich yet rigorous alternative to accounts of scientific knowledge based on formal logic, and he uses it to illuminate such topics as the nature of concepts, hypothesis formation, analogy, and theory justification.

Computational modelling of scientific discovery became known to a wider circle of reseachers in Europe through an excellent book titled Scientific Discovery: Computational Exploration of the Creative Processes, by Langley, Simon, Bradshaw and Zytkow ().Cited by: CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): In this paper we distinguish between two computational paradigms for knowledge discovery that share the notion of heuristic search, but dier in the importance they place on using scientific formalisms to state discovered knowledge.

We also report progress on computational methods for discovering such communicable. Computational Models Of Scientific Discovery And Theory Formation Computational Models Of Scientific Discovery And Theory Formation by Institute for the Study of Learning and Expertise. Download it Computational Models Of Scientific Discovery And Theory Formation books also available in PDF, EPUB, and Mobi Format for read it on your Kindle device, PC, phones or tablets.

Computational Discovery of Scientific Knowledge, Introduction, Techniques, and Applications in Environmental and Life Sciences. Lecture Notes in Computer Science.

CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract. This chapter introduces the field of computational scientific discovery and provides a brief overview thereof.

We first try to be more specific about what scientific discovery is and also place it in the broader context of the scientific enterprise.

We discuss the components of scientific behavior, that is. Scientific discovery is often regarded as romantic and creative--and hence unanalyzable--whereas the everyday process of verifying discoveries is sober and more suited to analysis.

Yet this fascinating exploration of how scientific work proceeds argues that however sudden the moment of discovery may seem, the discovery process can be described and modeled.1/5(1). The contributions in this book provide the reader with a complete view of the different tools used in the analysis of data for scientific discovery.

Gaber has organized the presentation into four parts: Part I provides the reader with the necessary background in the disciplines on which scientific data mining and knowledge discovery are based. Symposium on Computational Discovery of Communicable Knowledge, held in Stanford, CA, USA in March More representative coverage of recent research in computational scientific discovery is achieved by a significant number of additional invited contributions.

ISBN Computational Discovery of Scientific Knowledge. 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.

Scientific Discovery examines the nature of scientific research and reviews the arguments for and against a normative theory of discovery; describes the evolution of the BACON programs, which discover quantitative empirical laws and invent new concepts; presents programs that discover laws in qualitative and quantitative data; and ties the 4/5(1).

This approach uses computational ideas to shed light on how scientific theories are discovered, evaluated, and used in explanations. Thagard describes a detailed computational model of problem solving and discovery that provides a conceptually rich yet rigorous alternative to accounts of scientific knowledge based on formal logic, and he uses.

The focus of this project was on computer-mediated or computational scientific knowledge discovery, taken broadly as any research processes enabled by digital computing technologies. Such technologies may include data mining, information retrieval and extraction, artificial intelligence, distributed grid computing, and others.

Computational Discovery Of Scientific Knowledge Introduction Techniques And Applications In Environmental And Life Sciences Lecture Notes In Computer Science Author + By Paul Thagard A cognitive science perspective on scientific development, drawing on philosophy, psychology, neuroscience, and computational modeling.

Scientific Discovery: Computational Explorations of the Creative Processes by Langley, Patrick W.; Bradshaw, Gary; Chicago, Univ Of; Zytkow, Jan M. and a great selection of related books, art and collectibles available now at Computational Science & Discovery is an international, multidisciplinary journal focused on scientific advances and discovery through computational science in physics, chemistry, biology and applied science.

Computational Science & Discovery will cease publication with the volume. For further details on this decision, please visit https. Research on computational scientific discovery covers many forms of laws and models. Books on Scientific Discovery environment for the modeling and discovery of scientific knowledge.

International Journal of Human-Computer Studies, 64, The International Journal of Knowledge Discovery in Bioinformatics (IJKDB) collects the most significant research and latest practices in computational knowledge discovery approaches to.

Computational science, also known as scientific computing or scientific computation (SC), is a rapidly growing field that uses advanced computing capabilities to understand and solve complex problems.

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It is an area of science which spans many disciplines, but at its core, it involves the development of models and simulations to understand natural systems. Thus, Computational Social Science showcases the innovative methodological tools being developed and applied by leading researchers in this new field.

The book shows how academics and the private sector are using many of these tools to solve problems in social science and public policy."The contributions in this book provide the reader with a complete view of the different tools used in the analysis of data for scientific discovery.

Gaber has organized the presentation into four parts: Part I provides the reader with the necessary background in the disciplines on which scientific data mining and knowledge discovery are based.ngdm - Free download as Powerpoint Presentation .ppt), PDF File .pdf), Text File .txt) or view presentation slides online.