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Knowledge Representing and Clustering in e-Learning

  • Chunhua Ju
  • Xun Wang
  • Biwei Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3942)

Abstract

For e-Learning, traditional navigator or searching engine has inherent weaknesses, so individualized intelligent learning is difficult to be realized. This paper proposed a hybrid knowledge structure reflecting the relationships among knowledge modules. A series of association knowledge items were gathered by standardized inputting and knowledge clustering based on association rules. Based on the mapping of knowledge items to knowledge domain, the proposed knowledge clustering and representation could intelligently provide learner clues of interrelated learning. The simulation results showed that the proposed plan is an effective scheme of intelligent learning.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chunhua Ju
    • 1
  • Xun Wang
    • 1
  • Biwei Li
    • 1
  1. 1.College of Computer & Information EngineeringZhejiang Gongshang UniversityHangzhouP.R. China

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