Customer purchase prediction is increasingly recognized as a crucial marketing strategy in
B2C e-business, promising enhanced business profitability and customer satisfaction …

We study the problem of representing and recommending products for grocery shop**.
We carefully investigate grocery transaction data and observe three important patterns …

Multi-behavior session-based recommendation aims to predict the next item, such as a
location-based service (LBS) or a product, to be interacted by a specific behavior type (eg …

Recent research has suggested different metrics to measure the inconsistency of
recommendation performance, including the accuracy difference between user groups …

A point of interest (POI) recommender system (RS) is one of the representative research
areas based on the location-based social network (LBSN). Most POI RS studies utilized …

Displaying appropriate explanations for recommended items is of vital importance for
improving the persuasiveness and user satisfaction of recommender systems. Although a …

Given a user's historical interaction sequence, online novel recommendation suggests the
next novel the user may be interested in. Online novel recommendation is important but …

Online behavior recommendation is an attractive research topic related to social media
mining. This topic focuses on suggesting suitable behaviors for users in online platforms …

Human beings are creatures of habit. In their daily life, people tend to repeatedly consume
similar types of food items over several days and occasionally switch to consuming different …

A common question in forensic analysis is whether two observed data sets originated from
the same source or from different sources. Statistical approaches to addressing this question …