By Topic

Discipline-Ontology Based Learning Resources Semantic Retrieval Algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Yang Qing ; Sch. of Comput. Sci. & Technol., Wuhan Univ. of Technol., Wuhan, China ; Xiao Jiaquan

There is much difference among learners and learning resource providers when the semantic of learning resources is understood and expressed, and it is the important reason which causes lower accuracy in learning resources retrieval. In order to resolve the problem above, three mechanisms are applied as follows: 1) Discipline Ontology is constructed, which is the formalization for concepts and the relationships between concepts existing in some discipline domain. OWL is adopted as Discipline Ontology description language; 2) Inference rules are defined on the basis of Discipline Ontology. Semantic extension on keyword from user is performed by using Jena inference engine and inference rules , so as to better interpret and describe the requirement; 3) Learning resource metadata is extracted and defined by following Learning Resource Meta-data Specification, so as to provide formal description for learning resources. A semantic retrieval framework for learning resources is presented, and the process of learning resource semantic retrieval algorithm is discussed in detail. Firstly, the semantic extension on inquiry keyword from user is performed on the basis of Discipline Ontology; secondly, by using the improved similarity calculating formula, the keywords produced by semantic extension are sequenced. A set of keywords which have higher similarity with inquiry keyword are sorted out, and are used as inquiry keywords; then, search is performed on the basis of inquiry keywords and learning resource metadata. A set of descriptions for learning resources, which probably meet the requirement of user, is sent to user. The algorithm provides an approach for learning resource retrieval, and is able to support the effective access on learning resources.

Published in:

Internet Technology and Applications, 2010 International Conference on

Date of Conference:

20-22 Aug. 2010