Marco Avolio, Potito Aghilar, Sabino Roccotelli, Vito Walter Anelli, Chiara Mallamaci, Vincenzo Paparella, Marco Valentini, Alejandro Bellogín, Michelantonio Trizio, Joseph Trotta, Antonio Ferrara, Tommaso Di Noia
WarpRec is a new framework that unifies academic and industrial approaches to recommender systems, offering a scalable, sustainable, and efficient solution with over 50 algorithms and real-time energy tracking.
WarpRec is a new tool designed to improve the development of recommendation systems, which are used to suggest products or content to users. It solves the problem of having to choose between easy but limited research methods and complex, costly industrial systems by providing a flexible framework that works in both environments. WarpRec includes a wide range of algorithms and metrics, and it tracks energy usage to promote sustainability. This makes it a powerful tool for both researchers and companies, and it is designed to adapt to future technologies, such as AI that can interact more dynamically with users.
