Layered evaluation for data discovery and recommendation systems: An initial set of principles
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Authors
Manouselis, N.
Karagiannidis, C.
Sampson, Demetrios
Date
2014Type
Conference Paper
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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
ISBN
School
School of Education
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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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