Recommender Systems Evaluator: A Framework for Evaluating the Performance of Recommender Systems

Book chapter


dos Santos, Paulo V.G., Tardiole Kuehne, Bruno, Batista, Bruno G., Leite, Dionisio M., Peixoto, Maycon L.M., Moreira, Edmilson Marmo and Reiff-Marganiec, Stephan 2021. Recommender Systems Evaluator: A Framework for Evaluating the Performance of Recommender Systems. in: Springer.
Authorsdos Santos, Paulo V.G., Tardiole Kuehne, Bruno, Batista, Bruno G., Leite, Dionisio M., Peixoto, Maycon L.M., Moreira, Edmilson Marmo and Reiff-Marganiec, Stephan
Abstract

Recommender systems are filters that suggest products of interest to customers, which may positively impact sales. Nowadays, there is a multitude of algorithms for recommender systems, and their performance varies widely. So it is crucial to choose the most suitable option given a situation, but it is not a trivial task. In this context, we propose the Recommender Systems Evaluator (RSE): a framework aimed to accomplish an offline performance evaluation of recommender systems. We argue that the usage of a proper methodology is crucial when evaluating the available options. However, it is frequently overlooked, leading to inconsistent results. To help appraisers draw reliable conclusions, RSE is based on statistical concepts and displays results intuitively. A comparative study of classical recommendation algorithms is presented as an evaluation, highlighting RSE’s critical features.

KeywordsRecommender Systems; Collaborative Filtering; Parameter Optimization; Performance Evaluation
Year2021
PublisherSpringer
ISBN9783030704162
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-030-70416-2_43
Web address (URL)http://hdl.handle.net/10545/625853
http://creativecommons.org/publicdomain/zero/1.0/
hdl:10545/625853
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Publication dates05 Jun 2021
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Deposited29 Jun 2021, 16:37
Accepted11 Dec 2020
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ContributorsUniversity of Derby, Federal University of Itajubá, Itajubá, Brazil, Federal University of Mato Grosso do Sul (UFMS), Ponta Porã, Brazil, Federal University of Bahia (UFBA), Salvador, Brazil, University of Campinas, Campinas, Brazil and University of Derby
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