• DocumentCode
    3637593
  • Title

    Finding Patterns of Students´ Behavior in Synthetic Social Networks

  • Author

    Gamila Obadi;Pavla Dráždilová;Jan Martinovic;Katerina Slaninová;Václav Snášel

  • Author_Institution
    Dept. of Comput. Sci., Tech. Univ. of Ostrava, Ostrava, Czech Republic
  • fYear
    2010
  • Firstpage
    411
  • Lastpage
    413
  • Abstract
    Spectral clustering is a data mining method used for finding patterns in high dimensional datasets. It has been applied effectively to solve many problems in signal processing, bioinformatics, etc. In this paper spectral clustering was implemented to find students’ patterns of behavior in an elearning system, to explore the relationship between the similarity of students’behavior and their academic performance.
  • Keywords
    "Microeconomics","Laplace equations","Eigenvalues and eigenfunctions","Social network services","Data mining","Clustering algorithms","Electronic learning"
  • Publisher
    ieee
  • Conference_Titel
    Advances in Social Networks Analysis and Mining (ASONAM), 2010 International Conference on
  • Print_ISBN
    978-1-4244-7787-6
  • Type

    conf

  • DOI
    10.1109/ASONAM.2010.63
  • Filename
    5563070