Recommender Systems Evaluator: A Framework for Evaluating the Performance of Recommender Systems
Book chapter
Authors | 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 |
---|---|
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. |
Keywords | Recommender Systems; Collaborative Filtering; Parameter Optimization; Performance Evaluation |
Year | 2021 |
Publisher | Springer |
ISBN | 9783030704162 |
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 | |
File | File Access Level Open |
File | File Access Level Open |
File | |
Publication dates | 05 Jun 2021 |
Publication process dates | |
Deposited | 29 Jun 2021, 16:37 |
Accepted | 11 Dec 2020 |
Rights | CC0 1.0 Universal |
Contributors | University 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 |
https://repository.derby.ac.uk/item/9352z/recommender-systems-evaluator-a-framework-for-evaluating-the-performance-of-recommender-systems
Download files
67
total views24
total downloads1
views this month1
downloads this month
Export as
Related outputs
A unified graph model based on molecular data binning for disease subtyping
Hassan Zada, M., Yuan, B, Khan, W., Anjum, A., Reiff-Marganiec, S. and Saleem, R. 2022. A unified graph model based on molecular data binning for disease subtyping. Journal of Biomedical Informatics. pp. 1-24. https://doi.org/10.1016/j.jbi.2022.104187Learning Disease Causality Knowledge from Web of Health Data
Yu, H. and Reiff-Marganiec, S. 2022. Learning Disease Causality Knowledge from Web of Health Data. International journal on semantic web and information systems. 18 (1), pp. 1-19. https://doi.org/10.4018/IJSWIS.297145
Large-scale Data Integration Using Graph Probabilistic Dependencies (GPDs)
Zada, Muhammad Sadiq Hassan, Yuan, Bo, Anjum, Ashiq, Azad, Muhammad Ajmal, Khan, Wajahat Ali and Reiff-Marganiec, Stephan 2020. Large-scale Data Integration Using Graph Probabilistic Dependencies (GPDs). IEEE. https://doi.org/10.1109/bdcat50828.2020.00028Targeted ensemble machine classification approach for supporting IOT enabled skin disease detection
Yu, Hong Qing and Reiff-Marganiec, Stephan 2021. Targeted ensemble machine classification approach for supporting IOT enabled skin disease detection. IEEE Access. https://doi.org/10.1109/ACCESS.2021.3069024Performance evaluation of machine learning techniques for fault diagnosis in vehicle fleet tracking modules
Sepulevene, Luis, Drummond, Isabela, Kuehne, Bruno Tardiole, Frinhani, Rafael, Filho, Dionisio Leite, Peixoto, Maycon, Reiff-Marganiec, Stephan and Batista, Bruno 2021. Performance evaluation of machine learning techniques for fault diagnosis in vehicle fleet tracking modules. The Computer Journal. https://doi.org/10.1093/comjnl/bxab047
A repairing missing activities approach with succession relation for event logs
Liu, Jie, Xu, Jiuyun, Zhang, Ruru and Reiff-Marganiec, Stephan 2020. A repairing missing activities approach with succession relation for event logs. Knowledge and Information Systems. https://doi.org/10.1007/s10115-020-01524-6
A multi-objective optimized service level agreement approach applied on a cloud computing ecosystem
Azevedo, Leonildo Jose de Melo de, Estrella, Julio C., Toledo, Claudia F. Motta and Reiff-Marganiec, Stephan 2020. A multi-objective optimized service level agreement approach applied on a cloud computing ecosystem. IEEE Access. https://doi.org/10.1109/ACCESS.2020.3006171