Building Domain Ontologies from Text for Educational Purposes

被引:42
|
作者
Zouaq, Amal [1 ]
Nkambou, Roger [1 ]
机构
[1] Univ Quebec, GDAC Lab, Montreal, PQ H2X 3P2, Canada
来源
关键词
Applications and expert knowledge-intensive systems (education); intelligent Web services and Semantic Web knowledge acquisition; knowledge reuse;
D O I
10.1109/TLT.2008.12
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper presents a semiautomatic framework that aims to produce domain concept maps from text and then to derive domain ontologies from these concept maps. This methodology particularly targets the e-learning and Artificial Intelligence in Education (AIED) communities as they need such structures to sustain the production of e-learning resources tailored to learners' needs. This paper details the steps to transform textual resources, particularly textual learning objects (LOs), into domain concept maps, and it explains how this abstract structure is transformed into a formal domain ontology. A methodology is also presented to evaluate the results of ontology learning. The paper shows how such structures (domain concept maps and formal ontologies) make it possible to bridge the gap between e-learning and Intelligent Tutoring Systems by providing a common domain model.
引用
收藏
页码:49 / 62
页数:14
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