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Título
Hybrid system for video game recommendation based on implicit ratings and social networks
Autor(es)
Palabras clave
Recommender systems
Colaborative filtering
Content-based filtering
Rating estimation
Graph-based methods
Video games
Fecha de publicación
2020-01-17
Editor
Springer
Citación
Pérez-Marcos, J., Martín-Gómez, L., Jiménez-Bravo, D. M., López, V. F., & Moreno-García, M. N. (2020). Hybrid system for video game recommendation based on implicit ratings and social networks. Journal of Ambient Intelligence and Humanized Computing, 11(11), 4525-4535. https://doi.org/10.1007/S12652-020-01681-0
Serie / N.º
Journal of Ambient Intelligence and Humanized Computing.;Volume 11(11)
Resumen
[EN]The digital entertainment sector is one of the fastest growing in recent years. In the case of video games, the productions of some of the most popular titles are on a par with film productions. The sale of video games is in the millions, and yet there are few works on the recommendation of video games. In this work a hybrid system of video game recommendation is presented, through the use of collaborative filtering and content-based filtering, and the construction of relationship graphs. In order to improve the recommendations, a new method for estimating implicit ratings is proposed that takes into account the hours of play. The proposed recommender system improves the results of other techniques presented in the state of the art.
URI
ISSN
1868-5145, 1868-5137
Versión del editor
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