DocumentCode
2915498
Title
A similarity-based approach to enhance learning objects management systems
Author
Menendez-Dominguez, Victor H. ; Zapata, Alfredo ; Prieto-Mendez, Manuel E. ; Romero, Cristobal ; Serrano-Guerrero, Jesús
Author_Institution
Fac. of Math., Univ. of Yucatan, Merida, Mexico
fYear
2011
fDate
22-24 Nov. 2011
Firstpage
996
Lastpage
1001
Abstract
The Learning Object Repository is an important element in the management, publishing, location and retrieval of Learning Objects. However in this system, the task of finding Learning Objects that conform to user´s needs and requirements still presents problems related to easiness, simplicity and usefulness in selecting and recovering them. Thus, this paper proposes a metric to determine the similarity among Learning Objects based on information represented in their metadata. The proposed method is based on a fuzzy approach to determine the semantic similarity of XML structures used to represent the Learning Object metadata. The metric has been implemented into a Learning Object Management System, as part of the Searching component. This component offers several searching mechanisms based on Semantic Query, Learning Objects Patterns and Query by Examples. The first results confirm the effectiveness of the approach in identifying similar Learning Objects, an important task in managing these educational resource types.
Keywords
XML; computer aided instruction; meta data; XML structures; fuzzy approach; learning object metadata; learning object repository; learning objects management system enhancement; searching component; similarity based approach; Correlation; Measurement; Natural languages; Search problems; Semantics; Vocabulary; XML; Semantic similarity; learning object; management; searching;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems Design and Applications (ISDA), 2011 11th International Conference on
Conference_Location
Cordoba
ISSN
2164-7143
Print_ISBN
978-1-4577-1676-8
Type
conf
DOI
10.1109/ISDA.2011.6121788
Filename
6121788
Link To Document