The task of next basket recommendation is pivotal for recommender systems. It involves
predicting user actions, such as the next product purchase or movie selection, by exploring …

Next basket recommendation is a crucial task in market basket analysis. Given a user's
purchase history, usually a sequence of transaction data, one attempts to build a …

Basket representation plays an important role in the task of next-basket recommendation.
However, existing methods generally adopt pooling operations to learn a basket's …

Traditional approaches to next item and next basket recommendation typically extract users'
interests based on their past interactions and associated static contextual information (eg a …

Next-basket Recommendation (NBR) refers to the task of predicting a set of items that a user
will purchase in the next basket. However, most of existing works merely focus on the …

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 …

Predicting the next item that users may engage in is a key task of recommender systems,
and many methods have been proposed to deal with this task from different aspects …

Abstract Next Basket Recommendation system analyzes users' past interactions to provide
personalized recommendations. For a better understanding of the complex relations …

The next basket recommendation task aims to predict the items in the user's next basket by
modeling the user's basket sequence. Existing next basket recommendations focus on …