4 papers
DS4RS: Community-Driven and Explainable Dataset Search Engine for Recommender System Research
Xinyang Shao, Tri Kurniawan Wijaya
Accessing suitable datasets is critical for research and development in recommender systems. However, finding datasets that match specific recommendation task or domains remains a…
Universal Reusability in Recommender Systems: The Case for Dataset- and Task-Independent Frameworks
Tri Kurniawan Wijaya, Xinyang Shao, Gonzalo Fiz Pontiveros +1
Recommender systems are pivotal in delivering personalized experiences across industries, yet their adoption and scalability remain hindered by the need for extensive dataset- and…
Dataset-Agnostic Recommender Systems
Tri Kurniawan Wijaya, Edoardo D'Amico, Xinyang Shao
Recommender systems have become a cornerstone of personalized user experiences, yet their development typically involves significant manual intervention, including dataset-specific…
RBoard: A Unified Platform for Reproducible and Reusable Recommender System Benchmarks
Xinyang Shao, Edoardo D'Amico, Gabor Fodor +1
Recommender systems research lacks standardized benchmarks for reproducibility and algorithm comparisons. We introduce RBoard, a novel framework addressing these challenges by prov…