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: Foundations and Advances in Data Mining
  name:
    name part: Chu, Wesley.
    role:
      role term: editor.
  name:
    name part: Lin, Tsau Young.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2005
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 342 p. online resource.
  abstract: With the growing use of information technology and the recent advances in web systems, the amount of data available to users has increased exponentially. Thus, there is a critical need to understand the content of the data. As a result, data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this carefully edited volume a theoretical foundation as well as important new directions for data-mining research are presented. It brings together a set of well respected data mining theoreticians and researchers with practical data mining experiences. The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.
  table of contents: The Mathematics of Learning -- Logical Regression Analysis: From Mathematical Formulas to Linguistic Rules -- A Feature/Attribute Theory for Association Mining and Constructing the Complete Feature Set -- A New Theoretical Framework for K-means-type Clustering -- Clustering via Decision Tree Construction -- Incremental Mining on Association Rules -- Mining Association Rules from Tabular Data Guided by Maximal Frequent Itemsets -- Sequential Pattern Mining by Pattern-Growth: Principles and Extensions -- Web Page Classification -- Web Mining – Concepts, Applications, and Research Directions -- Privacy-Preserving Data Mining.
  note: edited by Wesley Chu, Tsau Young Lin.
  subject:
    topic: Computer science
  subject:
    topic: Computers
  subject:
    topic: Artificial intelligence
  subject:
    topic: Information theory
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Computer Science
  subject:
    topic: Theory of Computation
  subject:
    topic: Appl.Mathematics/Computational Methods of Engineering
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Information Systems and Communication Service
  subject:
    topic: Information and Communication, Circuits
  classification: QA75.5-76.95
  classification: 004.0151
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Fuzziness and Soft Computing, 180
  identifier: 9783540323938
  identifier: http://dx.doi.org/10.1007/b104039
  record info:
    record creation date: 100806
    record change date: 20151204144535.0
    record identifier: 978-3-540-32393-8