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    • Revista IJIMAI
    • 2024
    • vol. 8, nº 6, june 2024
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    • Revista IJIMAI
    • 2024
    • vol. 8, nº 6, june 2024
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    Comprehensive Evaluation of Matrix Factorization Models for Collaborative Filtering Recommender Systems

    Autor: 
    Bobadilla, Jesús
    ;
    Dueñas-Lerín, Jorge
    ;
    Ortega, Fernando
    ;
    Gutiérrez, Abraham
    Fecha: 
    06/2024
    Palabra clave: 
    collaborative filtering; matrix factorization; recommendation systems; IJIMAI
    Revista / editorial: 
    International Journal of Interactive Multimedia and Artificial Intelligence
    Citación: 
    Jesús Bobadilla, Jorge Dueñas-Lerín, Fernando Ortega, Abraham Gutiérrez (2024). "Comprehensive Evaluation of Matrix Factorization Models for Collaborative Filtering Recommender Systems", International Journal of Interactive Multimedia and Artificial Intelligence, vol. 8, issue Regular Issue, no. 6, pp. 15-23. https://doi.org/10.9781/ijimai.2023.04.008
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/14594
    DOI: 
    https://doi.org/10.9781/ijimai.2023.04.008
    Open Access
    Resumen:
    Matrix factorization models are the core of current commercial collaborative filtering Recommender Systems. This paper tested six representative matrix factorization models, using four collaborative filtering datasets. Experiments have tested a variety of accuracy and beyond accuracy quality measures, including prediction, recommendation of ordered and unordered lists, novelty, and diversity. Results show each convenient matrix factorization model attending to their simplicity, the required prediction quality, the necessary recommendation quality, the desired recommendation novelty and diversity, the need to explain recommendations, the adequacy of assigning semantic interpretations to hidden factors, the advisability of recommending to groups of users, and the need to obtain reliability values. To ensure the reproducibility of the experiments, an open framework has been used, and the implementation code is provided.
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