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Semantic Relatedness Measures in E-learning: A study

International Journal of Computer Applications
© 2013 by IJCA Journal
Volume 74 - Number 16
Year of Publication: 2013
R. Sunitha
G. Aghila

R Sunitha and G Aghila. Article: Semantic Relatedness Measures in E-learning: A study. International Journal of Computer Applications 74(16):39-43, July 2013. Full text available. BibTeX

	author = {R. Sunitha and G. Aghila},
	title = {Article: Semantic Relatedness Measures in E-learning: A study},
	journal = {International Journal of Computer Applications},
	year = {2013},
	volume = {74},
	number = {16},
	pages = {39-43},
	month = {July},
	note = {Full text available}


In this paper, a detailed study of works that have been carried out in finding the semantic relatedness or relatedness (in short) of Learning Objects (LO) in the context of E-learning has been presented. Learning Objects are small instructional chunks of learning elements which can be archived, extracted and shared in the learning process. Semantic relatedness in general specifies the degree of relatedness between two concepts in a taxonomy computed using different types of relations defined between the concepts. Semantic relatedness measures have been used in applications like Word sense Disambiguation, Information Retrieval, Natural Language Processing, Query Expansion etc. In the context of E-learning, there are several scenarios like learning object sequencing, query answering, scaffolding, clustering etc. where the computation of semantic relatedness between LO has promising scope. But only few works have been carried out in the quantification of semantic relatedness between LO. The objective of this paper is to present the existing semantic relatedness measures in general and with respect to learning object in specific and to analyze the adeptness of the measures.


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