Towards Human-Centric Psychomotor Recommender Systems

Portaz, Miguel; Manjarrés, Ángeles; Santos, Olga C.

doi:10.1145/3563359.3596993

Cited by 7 publications

(1 citation statement)

References 27 publications

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“…With the collected information, corresponding measures are determined on the basis of constraints matching user answers with potential service improvement trainings. Finally, Portaz et al [100] introduce an approach to the CF-based recommendation of psychomotor training practices in various contexts such as physical rehabilitation, keeping active when getting older, and different types of basic performance improvements goals also including professionals seeking to increase their excellence.…”

Section: Focused Trainingsmentioning

confidence: 99%

Sports Recommender Systems: Overview and Research Issues

Felfernig,

Wundara,

Tran

et al. 2023

Preprint

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Sports recommender systems receive an increasing attention due to their potential of fostering healthy living, improving personal well-being, and increasing performances in sport. These systems support people in sports, for example, by the recommendation of healthy and performance-boosting food items, the recommendation of training practices, talent and team recommendation, and the recommendation of specific tactics in competitions. With applications in the virtual world, for example, the recommendation of maps or opponents in e-sports, these systems already transcend conventional sports scenarios where physical presence is needed. On the basis of different working examples, we present an overview of sports recommender systems applications and techniques. Overall, we analyze the related state-of-the-art and discuss open research issues.

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Section: Focused Trainingsmentioning

confidence: 99%