DocumentCode :
2709904
Title :
Ontology Enabled Learning Resource Modeling and Management
Author :
Yang, Zongkai ; Huang, Tao ; Liu, Qingtang ; Li, Xia ; Wu, Bei
Author_Institution :
Dept. of Inf. Technol., Central China Normal Univ., Wuhan, China
fYear :
2006
fDate :
1-3 Nov. 2006
Firstpage :
100
Lastpage :
100
Abstract :
In this paper, we proposed the learning resource ontology(LRO) models to formally describe learning content and learning context, respectively. In addition to utilizing the models to formally describe content, we also derived ontological relation between the content and context at semantic level. Furthermore, we have built a semantic similarity algorithm to measure the similarity between ontologies. Based on the similarity measure, the process of LRO retrieval is presented.
Keywords :
information retrieval; learning (artificial intelligence); ontologies (artificial intelligence); resource allocation; LRO retrieval; learning content formal description; learning context formal description; ontology enabled learning resource management; ontology enabled learning resource modeling; semantic similarity algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Semantics, Knowledge and Grid, 2006. SKG '06. Second International Conference on
Conference_Location :
Guilin
Print_ISBN :
0-7695-2673-X
Type :
conf
DOI :
10.1109/SKG.2006.66
Filename :
5727737
Link To Document :
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