• DocumentCode
    797142
  • Title

    Toward a Fuzzy Domain Ontology Extraction Method for Adaptive e-Learning

  • Author

    Lau, Raymond Y K ; Song, Dawei ; Li, Yuefeng ; Cheung, Terence C H ; Hao, Jin-Xing

  • Author_Institution
    Dept. of Inf. Syst., City Univ. of Hong Kong, Kowloon
  • Volume
    21
  • Issue
    6
  • fYear
    2009
  • fDate
    6/1/2009 12:00:00 AM
  • Firstpage
    800
  • Lastpage
    813
  • Abstract
    With the widespread applications of electronic learning (e-Learning) technologies to education at all levels, increasing number of online educational resources and messages are generated from the corresponding e-Learning environments. Nevertheless, it is quite difficult, if not totally impossible, for instructors to read through and analyze the online messages to predict the progress of their students on the fly. The main contribution of this paper is the illustration of a novel concept map generation mechanism which is underpinned by a fuzzy domain ontology extraction algorithm. The proposed mechanism can automatically construct concept maps based on the messages posted to online discussion forums. By browsing the concept maps, instructors can quickly identify the progress of their students and adjust the pedagogical sequence on the fly. Our initial experimental results reveal that the accuracy and the quality of the automatically generated concept maps are promising. Our research work opens the door to the development and application of intelligent software tools to enhance e-Learning.
  • Keywords
    Internet; computer aided instruction; data mining; fuzzy set theory; ontologies (artificial intelligence); text analysis; adaptive electronic learning; concept map; fuzzy domain ontology extraction method; online educational resource; online message; text mining; Domain ontology; Knowledge management applications; Linguistic processing; Modeling structured; Text mining; concept map; e-Learning.; fuzzy sets; ontology extraction; text mining; textual and multimedia data;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/TKDE.2008.137
  • Filename
    4564463