• DocumentCode
    2082581
  • Title

    Generator-Recognizer Networks: A unified approach to probabilistic databases

  • Author

    Chen, Ruiwen ; Mao, Yongyi ; Kiringa, Iluju

  • Author_Institution
    SITE, Univ. of Ottawa, Ottawa, ON, Canada
  • fYear
    2010
  • fDate
    1-6 March 2010
  • Firstpage
    169
  • Lastpage
    172
  • Abstract
    Under the tuple-level uncertainty paradigm, we introduce a novel graphical model, Generator-Recognizer Network (GRN), as a model for probabilistic databases. The GRN modeling framework extends existing graphical models of probabilistic databases and is capable of representing a much wider range of dependence structures.
  • Keywords
    statistical databases; uncertainty handling; dependence structures; generator recognizer networks; probabilistic databases; tuple level uncertainty paradigm; Databases; Graphical models; Power measurement; Random variables; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering (ICDE), 2010 IEEE 26th International Conference on
  • Conference_Location
    Long Beach, CA
  • Print_ISBN
    978-1-4244-5445-7
  • Electronic_ISBN
    978-1-4244-5444-0
  • Type

    conf

  • DOI
    10.1109/ICDE.2010.5447925
  • Filename
    5447925
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2082581