Next basket prediction attempts to provide sequential recommendations to users based on a
sequence of the user's previous purchases. Ideally, a good prediction model should be able …

Next basket recommendation becomes an increasing concern. Most conventional models
explore either sequential transaction features or general interests of users. Further, some …

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 …

Next basket prediction from historical purchases is quite a complex task, even for e-
commerce datasets with a low number of items that are being purchased repeatedly. Neural …

Recommending the right products is the central problem in recommender systems, but the
right products should also be recommended at the right time to meet the demands of users …

To predict what products customers will buy in next transaction is an important task. Existing
work in next-basket prediction can be summarized into two paradigms. One is the item …

There are various real-world applications for next-basket recommender systems. One of
them is guiding a website user who wants to buy anything toward a collection of items …

Next-basket recommendation (NBR) aims to recommend a set of items to a consumer
according to past shopping carts. NBR essientially a more general and complex form than …

Next-basket recommendation (NBR) is prevalent in e-commerce and retail industry. In this
scenario, a user purchases a set of items (a basket) at a time. NBR performs sequential …

Timeliness and contextual accuracy of recommendations are increasingly important when
delivering contemporary digital marketing experiences. Conventional recommender systems …