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Cognitive context and arguments from ontologies for learning

Panayioutou, C. and Bennett, B. (2008) Cognitive context and arguments from ontologies for learning. In: Eschenbach, C. and Grüninger, M., (eds.) Formal Ontology in Information Systems - Proceedings of the Fifth International Conference. FOIS-08, Oct 31st - Nov 3rd 2008, Saarbrücken, Germany. Frontiers in Artificial Intelligence and Applications (183). IOS Press , pp. 65-78. ISBN 978-1-58603-923-3

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Abstract

The deployment of learning resources on the web by different experts has resulted in the accessibility of multiple viewpoints about the same topics. In this work we assume that learning resources are underpinned by ontologies. Different formalizations of domains may result from different contexts, different use of terminology, incomplete knowledge or conflicting knowledge. We define the notion of cognitive learning context which describes the cognitive context of an agent who refers to multiple and possibly inconsistent ontologies to determine the truth of a proposition. In particular we describe the cognitive states of ambiguity and inconsistency resulting from incomplete and conflicting ontologies respectively. Conflicts between ontologies can be identified through the derivation of conflicting arguments about a particular point of view. Arguments can be used to detect inconsistencies between ontologies. They can also be used in a dialogue between a human learner and a software tutor in order to enable the learner to justify her views and detect inconsistencies between her beliefs and the tutor’s own. Two types of arguments are discussed, namely: arguments inferred directly from taxonomic relations between concepts, and arguments about the necessary and

Item Type: Proceedings Paper
Copyright, Publisher and Additional Information: IOS Press 2008. This is an author produced version of a paper published in 'Formal Ontology in Information Systems'. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Ontologies, reasoning, formal comparison
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Computing (Leeds)
Depositing User: Mrs Irene Rudling
Date Deposited: 19 Feb 2009 10:55
Last Modified: 08 Feb 2013 17:06
Published Version: http://dx.doi.org/10.3233/978-1-58603-923-3-65
Status: Published
Publisher: IOS Press
Refereed: Yes
Identification Number: 10.3233/978-1-58603-923-3-65
URI: http://eprints.whiterose.ac.uk/id/eprint/7825

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