A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis

Okoye, Kingsley and Tawil, Abdel-Rahman H. and Naeem, Usman and Lamine, Elyes (2015) A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis. In: High Performance Computing and Communications, 2014 IEEE 6th Intl Symp on Cyberspace Safety and Security, 2014 IEEE 11th Intl Conf on Embedded Software and Syst (HPCC,CSS,ICESS), 2014 IEEE Intl Conf on. IEEE, pp. 49-60.

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Abstract

Semantic reasoning can help solve the problem of regulating the evolving and static measures of knowledge at theoretical and technological levels. The technique has been proven to enhance the capability of process models by making inferences, retaining and applying what they have learned as well as discovery of new processes. The work in this paper propose a semantic rule-based approach directed towards discovering learners interaction patterns within a learning knowledge base, and then respond by making decision based on adaptive rules centred on captured user profiles. The method applies semantic rules and description logic queries to build ontology model capable of automatically computing the various learning activities within a Learning Knowledge-Base, and to check the consistency of learning object/data types. The approach is grounded on inductive and deductive logic descriptions that allows the use of a Reasoner to check that all definitions within the learning model are consistent and can also recognise which concepts that fit within each defined class. Inductive reasoning is practically applied in order to discover sets of inferred learner categories, while deductive approach is used to prove and enhance the discovered rules and logic expressions. Thus, this work applies effective reasoning methods to make inferences over a Learning Process Knowledge-Base that leads to automated discovery of learning patterns/behaviour.

Item Type: Book Section
Uncontrolled Keywords: Process model, Learning process ,Ontology ,Semantic reasoning
Subjects: G400 Computer Science
Divisions: Faculty of Computing, Engineering and the Built Environment
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology > Cyber Security
UoA Collections > UoA11: Computer Science and Informatics
Depositing User: Oana-Andreea Dumitrascu
Date Deposited: 29 Jun 2017 13:32
Last Modified: 29 Jun 2017 13:32
URI: http://www.open-access.bcu.ac.uk/id/eprint/4758

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