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    Layered evaluation for data discovery and recommendation systems: An initial set of principles

    Access Status
    Fulltext not available
    Authors
    Manouselis, N.
    Karagiannidis, C.
    Sampson, Demetrios
    Date
    2014
    Type
    Conference Paper
    
    Metadata
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    Citation
    Manouselis, N. and Karagiannidis, C. and Sampson, D. 2014. Layered evaluation for data discovery and recommendation systems: An initial set of principles, in Proceedings of 2014 IEEE 14th International Conference on Advanced Learning Technologies (ICALT 2014), Jul 7-10 2014, pp. 518-519. Athens: Institute of Electrical and Electronics Engineers.
    Source Title
    Proceedings - IEEE 14th International Conference on Advanced Learning Technologies, ICALT 2014
    DOI
    10.1109/ICALT.2014.152
    ISBN
    9781479940387
    School
    School of Education
    URI
    http://hdl.handle.net/20.500.11937/3461
    Collection
    • Curtin Research Publications
    Abstract

    © 2014 IEEE. This paper examines how a layered evaluation framework proposed for adaptive systems (AS) can be applied in the case of recommender systems (RecSys). Our analysis indicates that implementing a layered-based evaluation has the potential to facilitate a more detailed and informed evaluation of RecSys, allowing researchers and developers to better understand how to improve them.

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