Data infrastructures make it convenient to work with auxiliary information and enable seamless cross-modality comparisons.
A rich collection of iterators for easy stochastic optimization. Model implementations make use of Cython to achieve C/C++ performance.
Full control over random number generators, open-access to existing algorithms and built-in datasets for reproducible research.
If you use Cornac in a scientific publication, we would appreciate citations to the following papers:
Cornac: A Comparative Framework for Multimodal Recommender Systems, Salah et al., JMLR 21, pp. 1-5, 2020.
Exploring Cross-Modality Utilization in Recommender Systems, Truong et al., IEEE Internet Computing, 2021.