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: Rough – Granular Computing in Knowledge Discovery and Data Mining
  name:
    name part: Stepaniuk, Jarosław.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2008
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIV, 162 p. online resource.
  abstract: The book "Rough-Granular Computing in Knowledge Discovery and Data Mining" written by Professor Jaroslaw Stepaniuk is dedicated to methods based on a combination of the following three closely related and rapidly growing areas: granular computing, rough sets, and knowledge discovery and data mining (KDD). In the book, the KDD foundations based on the rough set approach and granular computing are discussed together with illustrative applications. In searching for relevant patterns or in inducing (constructing) classifiers in KDD, different kinds of granules are modeled. In this modeling process, granules called approximation spaces play a special rule. Approximation spaces are defined by neighborhoods of objects and measures between sets of objects. In the book, the author underlines the importance of approximation spaces in searching for relevant patterns and other granules on dfferent levels of modeling for compound concept approximations. Calculi on such granules are used for modeling computations on granules in searching for target (sub) optimal granules and their interactions on different levels of hierarchical modeling. The methods based on the combination of granular computing, the rough and fuzzy set approaches allow for an effcient construction of the high quality approximation of compound concepts.
  table of contents: I: Rough Set Methodology -- Rough Sets -- Data Reduction -- II: Classification and Clustering -- Selected Classification Methods -- Selected Clustering Methods -- A Medical Case Study -- III: Complex Data and Complex Concepts -- Mining Knowledge from Complex Data -- Complex Concept Approximations -- IV: Conclusions, Bibliography and Further Readings -- Concluding Remarks.
  note: by Jarosław Stepaniuk.
  subject:
    topic: Computer science
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computer-aided engineering
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Computer Science
  subject:
    topic: Computer-Aided Engineering (CAD, CAE) and Design
  subject:
    topic: Appl.Mathematics/Computational Methods of Engineering
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  classification: TA345-345.5
  classification: 620.00420285
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Computational Intelligence, 152
  identifier: 9783540708018
  identifier: http://dx.doi.org/10.1007/978-3-540-70801-8
  record info:
    record creation date: 100301
    record change date: 20151204170055.0
    record identifier: 978-3-540-70801-8