• DocumentCode
    517471
  • Title

    Study of Heuristic Search and Exhaustive Search in Search Algorithms of the Structural Learning

  • Author

    Hui, Liu ; Yonghui, Cao

  • Author_Institution
    Sch. of Comput. & Inf. Technol., Henan Normal Univ., Xinxiang, China
  • Volume
    1
  • fYear
    2010
  • fDate
    24-25 April 2010
  • Firstpage
    169
  • Lastpage
    171
  • Abstract
    Structural learning can be accomplished by utilizing a search algorithm over the possible network structures, because it is finding the best network that fits the available data and is optimally complex. In this paper, a greater importance is given to the search algorithm because we have assumed that the data will be complete. We focus on Two search algorithms are introduced to learn the structure of a Bayesian network in the paper. The heuristic search algorithm is simple and explores a limited number of network structures. On the other hand, the exhaustive search algorithm is complex and explores many possible network structures.
  • Keywords
    algorithm theory; belief networks; Bayesian network; exhaustive search; heuristic search; search algorithms; structural learning; Bayesian methods; Computer networks; Databases; Heuristic algorithms; Information technology; Maximum likelihood estimation; Technology management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Information Technology (MMIT), 2010 Second International Conference on
  • Conference_Location
    Kaifeng
  • Print_ISBN
    978-0-7695-4008-5
  • Electronic_ISBN
    978-1-4244-6602-3
  • Type

    conf

  • DOI
    10.1109/MMIT.2010.163
  • Filename
    5474249