Computational Discovery Of Scientific Knowledge
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Computational Discovery Of Scientific Knowledge
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Author : Saso Dzeroski
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-08-07
Computational Discovery Of Scientific Knowledge written by Saso Dzeroski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-07 with Language Arts & Disciplines categories.
This survey provides an introduction to computational approaches to the discovery of communicable scientific knowledge and details recent advances. It is partly inspired by the contributions of the International Symposium on Computational Discovery of Communicable Knowledge, held in Stanford, CA, USA in March 2001, a number of additional invited contributions provide coverage of recent research in computational discovery.
Computational Discovery Of Scientific Knowledge
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Author : Saso Dzeroski
language : en
Publisher: Springer
Release Date : 2009-09-02
Computational Discovery Of Scientific Knowledge written by Saso Dzeroski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-02 with Language Arts & Disciplines categories.
This survey provides an introduction to computational approaches to the discovery of communicable scientific knowledge and details recent advances. It is partly inspired by the contributions of the International Symposium on Computational Discovery of Communicable Knowledge, held in Stanford, CA, USA in March 2001, a number of additional invited contributions provide coverage of recent research in computational discovery.
The Future Of Scientific Knowledge Discovery In Open Networked Environments
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2013-01-13
The Future Of Scientific Knowledge Discovery In Open Networked Environments written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-13 with Science categories.
Digital technologies and networks are now part of everyday work in the sciences, and have enhanced access to and use of scientific data, information, and literature significantly. They offer the promise of accelerating the discovery and communication of knowledge, both within the scientific community and in the broader society, as scientific data and information are made openly available online. 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. These technological capabilities support computer-mediated knowledge discovery, which some believe is a new paradigm in the conduct of research. The emphasis was primarily on digitally networked data, rather than on the scientific, technical, and medical literature. The meeting also focused mostly on the advantages of knowledge discovery in open networked environments, although some of the disadvantages were raised as well. The workshop brought together a set of stakeholders in this area for intensive and structured discussions. The purpose was not to make a final declaration about the directions that should be taken, but to further the examination of trends in computational knowledge discovery in the open networked environments, based on the following questions and tasks: 1. Opportunities and Benefits: What are the opportunities over the next 5 to 10 years associated with the use of computer-mediated scientific knowledge discovery across disciplines in the open online environment? What are the potential benefits to science and society of such techniques? 2. Techniques and Methods for Development and Study of Computer-mediated Scientific Knowledge Discovery: What are the techniques and methods used in government, academia, and industry to study and understand these processes, the validity and reliability of their results, and their impact inside and outside science? 3. Barriers: What are the major scientific, technological, institutional, sociological, and policy barriers to computer-mediated scientific knowledge discovery in the open online environment within the scientific community? What needs to be known and studied about each of these barriers to help achieve the opportunities for interdisciplinary science and complex problem solving? 4. Range of Options: Based on the results obtained in response to items 1-3, define a range of options that can be used by the sponsors of the project, as well as other similar organizations, to obtain and promote a better understanding of the computer-mediated scientific knowledge discovery processes and mechanisms for openly available data and information online across the scientific domains. The objective of defining these options is to improve the activities of the sponsors (and other similar organizations) and the activities of researchers that they fund externally in this emerging research area. The Future of Scientific Knowledge Discovery in Open Networked Environments: Summary of a Workshop summarizes the responses to these questions and tasks at hand.
Scientific Discovery
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Author : Pat Langley
language : en
Publisher: MIT Press
Release Date : 1987
Scientific Discovery written by Pat Langley and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Computers categories.
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. Using the methods and concepts of contemporary information-processing psychology (or cognitive science) the authors develop a series of artificial-intelligence programs that can simulate the human thought processes used to discover scientific laws. The programs--BACON, DALTON, GLAUBER, and STAHL--are all largely data-driven, that is, when presented with series of chemical or physical measurements they search for uniformities and linking elements, generating and checking hypotheses and creating new concepts as they go along. 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 results together, suggesting how a combined and extended program might find research problems, invent new instruments, and invent appropriate problem representations. Numerous prominent historical examples of discoveries from physics and chemistry are used as tests for the programs and anchor the discussion concretely in the history of science.
Computational Discovery Of Scientific Knowledge
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Author : Saso Dzeroski
language : en
Publisher: Springer
Release Date : 2007-08-24
Computational Discovery Of Scientific Knowledge written by Saso Dzeroski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-24 with Language Arts & Disciplines categories.
This survey provides an introduction to computational approaches to the discovery of communicable scientific knowledge and details recent advances. It is partly inspired by the contributions of the International Symposium on Computational Discovery of Communicable Knowledge, held in Stanford, CA, USA in March 2001, a number of additional invited contributions provide coverage of recent research in computational discovery.
Scientific Discovery Processes In Humans And Computers
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Author : Morton Wagman
language : en
Publisher: Praeger
Release Date : 2000-05-30
Scientific Discovery Processes In Humans And Computers written by Morton Wagman and has been published by Praeger this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-05-30 with Psychology categories.
Wagman offers a critical analysis of current theory and research in the psychological and computational sciences, directed toward the elucidation of scientific discovery processes and structures. It discusses human scientific discovery processes, analyzes computer scientific discovery processes, and makes a comparative evaluation of the two. This work examines the scientific reasoning of the discoverers of the inhibition mechanism of gene control; scientific discovery heuristics used at different developmental levels; artificial intelligence and mathematical discovery; the ECHO system; the evolution of artificial intelligence discovery systems; the PAULI system; and the KEKADA system. It concludes with an examination of the extent to which computational discovery systems can emulate a set of 10 types of scientific problems.
Scientific Data Mining And Knowledge Discovery
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Author : Mohamed Medhat Gaber
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-09-19
Scientific Data Mining And Knowledge Discovery written by Mohamed Medhat Gaber and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-19 with Computers categories.
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.
Computational Models Of Scientific Discovery And Theory Formation
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Author : Jeff Shrager
language : en
Publisher: Morgan Kaufmann
Release Date : 1990
Computational Models Of Scientific Discovery And Theory Formation written by Jeff Shrager and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Computers categories.
This collection reports on recent advances in the study of scientific discovery and theory formation based on the computational techniques of artificial intelligence and cognitive science.
Knowledge Guided Machine Learning
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Author : Anuj Karpatne
language : en
Publisher: CRC Press
Release Date : 2022-08-15
Knowledge Guided Machine Learning written by Anuj Karpatne and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-15 with Business & Economics categories.
Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and data at an equal footing. Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness to the problem formulations and research methods in this emerging field. Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data provides an introduction to this rapidly growing field by discussing some of the common themes of research in KGML using illustrative examples, case studies, and reviews from diverse application domains and research communities as book chapters by leading researchers. KEY FEATURES First-of-its-kind book in an emerging area of research that is gaining widespread attention in the scientific and data science fields Accessible to a broad audience in data science and scientific and engineering fields Provides a coherent organizational structure to the problem formulations and research methods in the emerging field of KGML using illustrative examples from diverse application domains Contains chapters by leading researchers, which illustrate the cutting-edge research trends, opportunities, and challenges in KGML research from multiple perspectives Enables cross-pollination of KGML problem formulations and research methods across disciplines Highlights critical gaps that require further investigation by the broader community of researchers and practitioners to realize the full potential of KGML
Discovery Science
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Author : Sašo Džeroski
language : en
Publisher: Springer
Release Date : 2014-09-27
Discovery Science written by Sašo Džeroski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-27 with Computers categories.
This book constitutes the proceedings of the 17th International Conference on Discovery Science, DS 2014, held in Bled, Slovenia, in October 2014. The 30 full papers included in this volume were carefully reviewed and selected from 62 submissions. The papers cover topics such as: computational scientific discovery; data mining and knowledge discovery; machine learning and statistical methods; computational creativity; mining scientific data; data and knowledge visualization; knowledge discovery from scientific literature; mining text, unstructured and multimedia data; mining structured and relational data; mining temporal and spatial data; mining data streams; network analysis; discovery informatics; discovery and experimental workflows; knowledge capture and scientific ontologies; data and knowledge integration; logic and philosophy of scientific discovery; and applications of computational methods in various scientific domains.