The progress of recommender systems is hampered mainly by evaluation as it requires real- time interactions between humans and systems, which is too laborious and expensive. This …
Recommender Systems have shown to be an effective way to alleviate the over-choice problem and provide accurate and tailored recommendations. However, the impressive …
Scholars in algorithmic recommender systems research have developed a largely standardized scientific method, where progress is claimed by showing that a new algorithm …
D Roy, M Dutta - Journal of Big Data, 2022 - Springer
Recommender systems are efficient tools for filtering online information, which is widespread owing to the changing habits of computer users, personalization trends, and …
Recommender systems research is being slowed by the difficulty of replicating and comparing research results. Published research uses various experimental methodologies …
Offline evaluation is an essential complement to online experiments in the selection, improvement, tuning, and deployment of recommender systems. Offline methodologies for …
Recommender systems are among today's most successful application areas of artificial intelligence. However, in the recommender systems research community, we have fallen …
X Amatriain, J Basilico - Proceedings of the 10th ACM conference on …, 2016 - dl.acm.org
When the Netflix Prize launched in 2006, it put a spotlight on the importance and use of recommender systems in real-world applications. The competition provided many lessons …
While recent years have witnessed a rapid growth of research papers on recommender system (RS), most of the papers focus on inventing machine learning models to better fit …