You are here:

Layered Evaluation in Recommender Systems: A Retrospective Assessment
ARTICLE

, ,

Journal of e-Learning and Knowledge Society Volume 10, Number 1, ISSN 1826-6223 e-ISSN 1826-6223 Publisher: Italian e-Learning Association

Abstract

valuation of recommender systems has only lately started to become more systematic, since the emphasis has long been on the experimental evaluation of algorithmic performance. Recent studies have proposed adopting a layered evaluation approach, according to which recommender systems may be decomposed into several components, evaluating each of them separately. Nevertheless, there are still no evaluation studies of recommender systems that apply a layered evaluation framework to explore how all the different components or layers of such a system may be assessed. This paper introduces layered evaluation and examines how a previously proposed layered evaluation framework for adaptive systems can be applied in the case of recommender systems. It presents the possible adaptation of this out a retrospective analysis of its past evaluation results under the new prism that the layered evaluation approach brings. Our analysis indicates that implementing a layered- based evaluation of recommender systems has the potential to facilitate a more detailed and informed evaluation of such systems, allowing researchers and developers to better understand how to improve them.

Citation

Manouselis, N., Karagiannidis, C. & Sampson, D. (2014). Layered Evaluation in Recommender Systems: A Retrospective Assessment. Journal of e-Learning and Knowledge Society, 10(1),. Italian e-Learning Association. Retrieved January 26, 2020 from .

References

View References & Citations Map

These references have been extracted automatically and may have some errors. Signed in users can suggest corrections to these mistakes.

Suggest Corrections to References