What is it about?
The method in this book chapter shows that semantic reasoning can help solve the problem of regulating the evolving and static measures of knowledge at theoretical and technological levels.
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Why is it important?
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.
Perspectives
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
Dr Kingsley Okoye
University of East London
Read the Original
This page is a summary of: A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis, November 2015, Springer Science + Business Media,
DOI: 10.1007/978-3-319-27400-3_5.
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