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: Knowledge discovery for business information systems
  name:
    name part: Abramowicz, Witold.
  name:
    name part: Zurada, Jozef
    name part: 1949-
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: mau
    date issued: 2001
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xvii, 431 pages) : illustrations.
  abstract: Current database technology and computer hardware allow us to gather, store, access, and manipulate massive volumes of raw data in an efficient and inexpensive manner. In addition, the amount of data collected and warehoused in all industries is growing every year at a phenomenal rate. Nevertheless, our ability to discover critical, non-obvious nuggets of useful information in data that could influence or help in the decision making process, is still limited. Knowledge discovery (KDD) and Data Mining (DM) is a new, multidisciplinary field that focuses on the overall process of information discovery from large volumes of data. The field combines database concepts and theory, machine learning, pattern recognition, statistics, artificial intelligence, uncertainty management, and high-performance computing. To remain competitive, businesses must apply data mining techniques such as classification, prediction, and clustering using tools such as neural networks, fuzzy logic, and decision trees to facilitate making strategic decisions on a daily basis. Knowledge Discovery for Business Information Systems contains a collection of 16 high quality articles written by experts in the KDD and DM field from the following countries: Austria, Australia, Bulgaria, Canada, China (Hong Kong), Estonia, Denmark, Germany, Italy, Poland, Singapore and USA.
  note: edited by Witold Abramowicz, Jozef Zurada.
  note: Electronic resource.
  note: Includes bibliographical references and index.
  subject:
    topic: Data mining
  subject:
    topic: Knowledge acquisition (Expert systems)
  subject:
    topic: Database searching
  subject:
    topic: Computer science
  subject:
    topic: Data Structures, Cryptology and Information Theory
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Business Information Systems
  subject:
    topic: COMPUTERS
    topic: Enterprise Applications
    topic: Business Intelligence Tools
  subject:
    topic: COMPUTERS
    topic: Intelligence (AI) & Semantics
  subject:
    topic: Data mining
  subject:
    topic: Database searching
  subject:
    topic: Knowledge acquisition (Expert systems)
  subject:
    topic: Andre fag (naturvidenskab og teknik)
    topic: Andre fag
  classification: QA76.9.D343 K56 2001eb
  classification: 006.3
  related item:
    title info:
      title: Knowledge discovery for business information systems
    origin info:
      publisher: New York : Kluwer Academic Publishers, ©2001
    identifier: (DLC) 00048482
    identifier: (OCoLC)45080120
  related item:
    title info:
      title: Kluwer international series in engineering and computer science ; SECS 600
  identifier: 030646991X
  identifier: 9780306469916
  identifier: 9780792372431
  identifier: 0792372433
  identifier: https://proxy.library.tamu.edu/login
  related item:
    location:
      url: https://proxy.library.tamu.edu/login
  record info:
    record content source: N$T
    record creation date: 020917
    record change date: 20220105140520.0
    record identifier: in00001843329
    language of cataloging:
      language term: eng