In recent years, bundle recommendation systems have gained significant attention in both
academia and industry due to their ability to enhance user experience and increase sales by …

Item fairness of recommender systems aims to evaluate whether items receive a fair share of
exposure according to different definitions of fairness. Raj and Ekstrand study multiple …

There is a rapidly-growing research interest in modeling user preferences via pre-training
multi-domain interactions for recommender systems. However, Existing pre-trained multi …

Next-basket recommendation (NBR) aims to infer the items in the next basket given the
corresponding basket sequence. Existing NBR methods are mainly based on either …

As repetition of activities can establish habits and exploration of new ones can provide a
healthy variety, we investigate how a recommender system for physical activities can …

Next basket recommendation (NBR) is an essential task within the realm of recommendation
systems and is dedicated to the anticipation of user preferences in the next moment based …

Group recommendation (GR) plays a crucial role in social platforms, aiming to recommend
items to entire groups based on collective interaction behaviors. Existing GR models …

The goal of modern sequential recommender systems is often formulated in terms of next-
item prediction. In this paper, we explore the applicability of generative transformer-based …

In next basket recommendation (NBR) a set of items is recommended to users based on
their historical basket sequences. In many domains, the recommended baskets consist of …

Next Basket Recommendation (NBR) is a new type of recommender system that predicts
combinations of items users are likely to purchase together. Existing NBR models often …