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    Autonomic computing and ontologies to enable context-aware learning design

    Charlton, P. and Magoulas, George D. (2010) Autonomic computing and ontologies to enable context-aware learning design. In: UNSPECIFIED (ed.) IEEE International Conference on Tools with Artificial Intelligence. New York, USA: Institute of Electrical and Electronics Engineers, pp. 286-291. ISBN 9781424488179.

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    Abstract

    Semantic web technologies and autonomic computing principles are combined in this paper in an attempt to design and build a learning design environment that possesses context-aware features. Our approach builds on the features of self-management and organisation of autonomic computing but uses self-configuration as a means to extend a knowledge-based inference through the design of meta-level inference. Thus, the context inference is modelled using a meta-interpreter and self-configuration rules. The details of our approach are presented demonstrating the use of self-configurable inferencing to support the creation and use of context-paths across learning design domain concepts. The paths exploit ontology alignment principles to determine contextual relevance between user learning designs and core system knowledge.

    Metadata

    Item Type: Book Section
    School: School of Business, Economics & Informatics > Computer Science and Information Systems
    Research Centres and Institutes: Birkbeck Knowledge Lab
    Depositing User: Sarah Hall
    Date Deposited: 18 Jul 2013 13:15
    Last Modified: 02 Dec 2016 13:23
    URI: https://eprints.bbk.ac.uk/id/eprint/7723

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