Proceedings of the 4th Workshop on Online Recommender Systems and User Modeling -- ORSUM 2021. (arXiv:2201.05156v1 [cs.IR])

Modern online services continuously generate data at very fast rates. This
continuous flow of data encompasses content -- e.g., posts, news, products,
comments --, but also user feedback -- e.g., ratings, views, reads, clicks --,
together with context data -- user device, spatial or temporal data, user task
or activity, weather. This can be overwhelming for systems and algorithms
designed to train in batches, given the continuous and potentially fast change
of content, context and user preferences or intents. Therefore, …

arxiv modeling recommender systems systems