rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Scientific Data Mining and Knowledge Discovery
    sub title: Principles and Foundations
  name:
    name part: Gaber, Mohamed Medhat.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2010
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 400 p. online resource.
  abstract: With the evolution in data storage, large databases have stimulated researchers from many areas, especially machine learning and statistics, to adopt and develop new techniques for data analysis in different fields of science. In particular, there have been notable successes in the use of statistical, computational, and machine learning techniques to discover scientific knowledge in the fields of biology, chemistry, physics, and astronomy. With the recent advances in ontologies and knowledge representation, automated scientific discovery (ASD) has further, great prospects in the future. 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. Part II details applications of computational methods used in geospatial, chemical, and bioinformatics applications. Part III is about data mining applications in geosciences, chemistry, and physics. Finally, in Part IV, future trends and directions for research are explained. The book serves as a starting point for students and researchers interested in this multidisciplinary field. It offers both an overview of the state of the art and lists areas and open issues for future research and development.
  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.
  note: edited by Mohamed Medhat Gaber.
  subject:
    topic: Computer science
  subject:
    topic: Chemoinformatics
  subject:
    topic: Earth sciences
  subject:
    topic: Data mining
  subject:
    topic: Artificial intelligence
  subject:
    topic: Pattern recognition
  subject:
    topic: Computer mathematics
  subject:
    topic: Computer Science
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Computational Science and Engineering
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Pattern Recognition
  subject:
    topic: Computer Applications in Chemistry
  subject:
    topic: Earth Sciences, general
  classification: QA76.9.D343
  classification: 006.312
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783642027888
  identifier: http://dx.doi.org/10.1007/978-3-642-02788-8
  record info:
    record creation date: 100301
    record change date: 20151204184717.0
    record identifier: 978-3-642-02788-8