MCRecKit: An Open-Source Library for Multi-Criteria Recommendations
Yong Zheng, David Xuejun Wang, Qin Ruan · 2024
Recommender systems (RSs) are designed to help users navigate through large amounts of information by providing personalized suggestions tailored to their preferences. Multi-criteria recommender systems (MCRSs) extend this concept by utilizing users' ratings on multiple aspects of items (i.e., multi-criteria ratings) to predict their overall preferences. Currently, there are several open-source libraries released for RSs. However, none of these existing libraries can handle multi-criteria recommendations due to the special challenges in MCRSs. In this paper, we introduce a Multi-Criteria Recommendation Kit (MCRecKit) which is a Python-based open-source library for multi-criteria recommendations. MCRecKit fills the gap by providing flexible tools and algorithms specifically designed to address the complexity of MCRSs. The library offers a variety of methods for processing, modeling, and evaluating multi-criteria data, enabling researchers and developers to experiment with novel approaches.