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

被引:79
作者
Lau, Raymond Y. K. [1 ]
Song, Dawei [2 ]
Li, Yuefeng [3 ]
Cheung, Terence C. H. [1 ]
Hao, Jin-Xing [1 ]
机构
[1] City Univ Hong Kong, Dept Informat Syst, Kowloon, Hong Kong, Peoples R China
[2] Open Univ, Knowledge Media Inst, Milton Keynes MK7 6AA, Bucks, England
[3] Queensland Univ Technol, Fac Informat Technol, Brisbane, Qld 4001, Australia
基金
英国工程与自然科学研究理事会;
关键词
Domain ontology; ontology extraction; text mining; fuzzy sets; concept map; e-Learning; HIERARCHIES; INFORMATION; GENERATION; ALGORITHM;
D O I
10.1109/TKDE.2008.137
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:800 / 813
页数:14
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