• DocumentCode
    1841317
  • Title

    Probabilistic Relational Models with Relational Uncertainty: An Early Study in Web Page Classification

  • Author

    Fersini, E. ; Messina, E. ; Archetti, F.

  • Volume
    3
  • fYear
    2009
  • fDate
    15-18 Sept. 2009
  • Firstpage
    139
  • Lastpage
    142
  • Abstract
    In the last decade, new approaches focused on modelling uncertainty over complex relational data have been developed. In this paper one of the most promising of such approaches, known as Probabilistic Relational Models (PRMs), has been investigated and extended in order to measure and include uncertainty over relationships. Our extension, called PRMs with Relational Uncertainty, has been evaluated on real-data for web document classification purposes. Experimental results shown the potentiality of the proposed methods of capturing the real “strength” of relationships and the capacity of including this information into the probability model.
  • Keywords
    Bayesian methods; Capacity planning; Conferences; Informatics; Intelligent agent; Logic; Measurement uncertainty; Probability; Skeleton; Web pages; Keywords-Probabilistic Relational Models; Relational Uncertainty; Web Page Classification;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technologies, 2009. WI-IAT '09. IEEE/WIC/ACM International Joint Conferences on
  • Conference_Location
    Milan, Italy
  • Print_ISBN
    978-0-7695-3801-3
  • Electronic_ISBN
    978-1-4244-5331-3
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2009.249
  • Filename
    5284946