A Data Mining Approach for Managing Shared Ontological Knowledge


Lee, Chien-Sing and Kiu, Ching-Chieh (2006) A Data Mining Approach for Managing Shared Ontological Knowledge. In: Sixth International Conference on Advanced Learning Technologies, 2006. IEEE Xplore, 16 -18. ISBN 0-7695-2632-2

[img] Text
01652353.pdf - Published Version
Restricted to Repository staff only

Download (177kB)


Semantics are added to content components through ontological definitions to provide context to learning objects (LOs). Therefore, an ontological contextual environment facilitates knowledge management processes such as reusing, sharing, retrieving and indexing LOs for contextual learning in integrated learning environments. Consequently, contextual LOs from different learning object repositories can be more easily and meaningfully codified and exchanged through a shared ontology. This paper presents new ontological mapping and merging results using a hybrid data mining approach in our ontology mapping and merging method, OntoDNA. Different lexical measures are used to discover semantic similarity between ontological elements to generate a shared ontology. Accuracy in mapping and merging is measured using precision, recall, and f-measure. Significance of the study lies in the algorithm's scalability and in simple transformation of ontological attributes for data processing

Item Type: Book Section
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 21 Nov 2013 05:59
Last Modified: 21 Nov 2013 05:59
URII: http://shdl.mmu.edu.my/id/eprint/4457


Downloads per month over past year

View ItemEdit (login required)