• DocumentCode
    2710816
  • Title

    Spatiotemporal Relational Probability Trees: An Introduction

  • Author

    McGovern, Amy ; Hiers, Nathan C. ; Collier, Matthew ; Gagne, David J., II ; Brown, Rodger A.

  • Author_Institution
    Univ. of Oklahoma, OK
  • fYear
    2008
  • fDate
    15-19 Dec. 2008
  • Firstpage
    935
  • Lastpage
    940
  • Abstract
    We introduce spatiotemporal relational probability trees (SRPTs), probability estimation trees for relational data that can vary in both space and time. The SRPT algorithm addresses the exponential increase in search complexity through sampling. We validate the SRPT using a simulated data set and we empirically demonstrate the SRPT algorithm on two real-world data sets.
  • Keywords
    probability; relational databases; trees (mathematics); probability estimation trees; real-world data sets; spatiotemporal relational probability trees; Data mining; Decision trees; Discrete event simulation; Floods; Logic programming; Sampling methods; Space technology; Spatiotemporal phenomena; Storms; Tornadoes; spatiotemporal; statistical relational data mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, 2008. ICDM '08. Eighth IEEE International Conference on
  • Conference_Location
    Pisa
  • ISSN
    1550-4786
  • Print_ISBN
    978-0-7695-3502-9
  • Type

    conf

  • DOI
    10.1109/ICDM.2008.134
  • Filename
    4781204
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2710816