Predicting users' actions based on anonymous sessions is a challenging problem in web-
based behavioral modeling research, mainly due to the uncertainty of user behavior and the …

Session-based Recommendations recommend the next possible item for the user with
anonymous sessions, whose challenge is that the user's behavioral preference can only be …

Recommender systems (RS) have become an integral part of our daily life. However, most
current RS often repeatedly recommend items to users with similar profiles. We argue that …

In the intelligent transportation system, the session data usually represents the users'
demand. However, the traditional approaches only focus on the sequence information or the …

Session-based recommendation aims to predict next item based on users' anonymous
behavior sequence within a short time. Recent studies focus on modeling sequential …

Session-based recommendation is a challenging problem due to the inherent uncertainty of
user behavior and the limited historical click information. Latent factors and the complex …

Fairness is an important research problem for recommendation systems, and unfair
recommendation methods can lead to discrimination against users. Gender is a kind of …

In the current era of the rapid development of big data, it has become increasingly critical
and practical to study recommender systems with streaming data input. However, the …

Sequential recommendation, such as next-basket recommender systems (NBRS), which
model users' sequential behaviors and the relevant context/session, has recently attracted …

Recommender systems are becoming a crucial part of several websites. The purpose of
session-based recommendations is to predict the next item that users might click based on …