Next basket recommendation aims to infer a set of items that a user will purchase at the next
visit by considering a sequence of baskets he/she has purchased previously. This task has …

In data mining, Frequent Itemsets Mining is a technique used in several domains with
notable results. However, the large volume of data in modern datasets increases the …

Collective user behavior in social media applications often drives several important online
and offline phenomena linked to the spread of opinions and information. Several studies …

Human behaviors are complex, which are often observed as a sequence of heterogeneous
actions. In this paper, we take user choices for shop** baskets as a typical case to study …

The prediction of the Customer Lifetime Value (CLV) is an important asset for tool-supported
marketing by customer relationship managers. Since standard methods based on purchase …

Accurate estimation of customer lifetime value (LTV), which reflects the potential
consumption of a user over a period of time, is crucial for the revenue management of online …

User purchase behaviours are complex and dynamic, which are usually observed as
multiple choice actions across a sequence of shop** baskets. Most of the existing next …

To complement traditional dietary surveys, which are costly and of limited scale, researchers
have resorted to digital data to infer the impact of eating habits on people's health. However …

Next basket recommendation aims at predicting the next set of items that a user would likely
purchase together, which plays an important role in e-commerce platforms. Unlike …

Online games make up the largest segment of the booming global game market in terms of
revenue as well as players. Unlike games that sell games at one time for profit, online …