Issue No. 06 - June (2009 vol. 21)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2008.137
Raymond Y.K. Lau , City University of Hong Kong, Kowloon
Dawei Song , The Open University, Milton Keynes
Yuefeng Li , Queensland University of Technology, Brisbane
Terence C.H. Cheung , City University of Hong Kong, Kowloon
Jin-Xing Hao , City University of Hong Kong, Kowloon
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.
Domain ontology, ontology extraction, text mining, fuzzy sets, concept map, e-Learning.
J. Hao, R. Y. Lau, T. C. Cheung, D. Song and Y. Li, "Toward a Fuzzy Domain Ontology Extraction Method for Adaptive e-Learning," in IEEE Transactions on Knowledge & Data Engineering, vol. 21, no. , pp. 800-813, 2008.