Automating ontologies for e–learning. (7th July 2014)

• Record Type: Journal Article
• Authors: Suresh, R.M.; Dinakaran, K.; Amulya, Rebecca
• Is Part Of: International journal of metadata, semantics and ontologies. Volume 9:Number 3(2014)
• Page Start: 227
• Page End: 232
• Publication Date: 2014-07-07
• Subjects: ontologies -- manual approach -- semi–automatic approach -- automatic approach -- ontology construction -- e–learning -- ontological data mining -- online learning -- electronic learning -- dependency graphs; Metadata -- Periodicals; Semantic Web -- Periodicals; Ontologies (Information retrieval) -- Periodicals; Data structures (Computer science) -- Periodicals; Information theory -- Periodicals; 005.74
• Languages: English
• ISSNs: 1744-2621

Abstract

Electronic learning is gaining importance due to the emerging technologies. Many courseware repositories exist that cater to the need of the users, but they do not provide an automatic prerequisite and follow–up identification facility. This model is developed in such a way that it provides such a facility. The solution is obtained by implementing the project using ontological data mining concepts. Ontological data mining helps in the development of domain ontologies from text data automatically by using the term frequency–inverse document frequency method. Thus, the work is implemented in such a way that domain ontologies are generated for a given portable document format file so that the automatic prerequisite and follow–up identification becomes easy. The system extracts the concepts using term frequency–inverse document frequency weighting scheme and then determines the associations among concepts using a priori algorithm. These relationships are used to build the dependency graph which is finally imported to form domain ontology.