Recommender systems (RSs) have been playing an increasingly important role for informed
consumption, services, and decision-making in the overloaded information era and digitized …

Recent years have witnessed the remarkable success of recommendation systems (RSs) in
alleviating the information overload problem. As a new paradigm of RSs, session-based …

Sequential recommendation has become an attractive topic in recommender systems.
Existing sequential recommendation methods, including the methods based on the state-of …

Session-based Recommendation (SR) aims to predict the next item for recommendation
based on previously recorded sessions of user interaction. The majority of existing …

Recommender systems have become an important instrument to connect people to
information. Sparse, complex, and rapidly growing data presents new challenges to …

Session-based recommender systems (SBR) aim to predict the next action of an anonymous
user session. Recently Graph Neural Networks (GNN) models have gained a lot of attention …

We present a novel generative Session-Based Recommendation (SBR) framework, called
VAriational SEssion-based Recommendation (VASER)–a non-linear probabilistic …

Despite advances in deep learning methods for song recommendation, most existing
methods do not take advantage of the sequential nature of song content. In addition, there is …

We present a novel generative Session-Based Recommendation (SBR) framework, called
VAriational SEssion-based Recommendation (VASER)-a non-linear probabilistic …