In SIGIR'24, we've published an paper called Turbo-CF (Park et al., "Turbo-cf: Matrix decomposition-free graph filtering for fast recommendation." In SIGIR 2024). This is graph filtering-based, extremely simple to implement, yet powerful recommendation method. It only requires few lines of code for end-to-end running.
We would greatly appreciate it if the RecBole team could consider adding Turbo-CF to the RecBole model. This would enable more researchers and practitioners to easily access and apply this model for their recommendation tasks.
Refer to my code here: https://github.com/jindeok/Turbo-CF
Hi RecBole Team!
In SIGIR'24, we've published an paper called Turbo-CF (Park et al., "Turbo-cf: Matrix decomposition-free graph filtering for fast recommendation." In SIGIR 2024). This is graph filtering-based, extremely simple to implement, yet powerful recommendation method. It only requires few lines of code for end-to-end running.
We would greatly appreciate it if the RecBole team could consider adding Turbo-CF to the RecBole model. This would enable more researchers and practitioners to easily access and apply this model for their recommendation tasks. Refer to my code here: https://github.com/jindeok/Turbo-CF
Thank you for your time and consideration :)