• DocumentCode
    787151
  • Title

    A survey of temporal knowledge discovery paradigms and methods

  • Author

    Roddick, John F. ; Spiliopoulou, Myra

  • Author_Institution
    Sch. of Informatics & Eng., Flinders of Univ. of South Australia, Adelaide, SA, Australia
  • Volume
    14
  • Issue
    4
  • fYear
    2002
  • Firstpage
    750
  • Lastpage
    767
  • Abstract
    With the increase in the size of data sets, data mining has recently become an important research topic and is receiving substantial interest from both academia and industry. At the same time, interest in temporal databases has been increasing and a growing number of both prototype and implemented systems are using an enhanced temporal understanding to explain aspects of behavior associated with the implicit time-varying nature of the universe. This paper investigates the confluence of these two areas, surveys the work to date, and explores the issues involved and the outstanding problems in temporal data mining.
  • Keywords
    data mining; database theory; temporal databases; time series; very large databases; data sets; large databases; rule semantics; temporal data mining; temporal databases; temporal knowledge discovery paradigms; temporal rules; time sequence mining; trend analysis; Artificial intelligence; Association rules; Computer industry; Data mining; Databases; Helium; Mining industry; Prototypes; Time varying systems; Voting;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/TKDE.2002.1019212
  • Filename
    1019212