Recommender system is one of the most important information services on today's Internet.
Recently, graph neural networks have become the new state-of-the-art approach to …

Influenced by the great success of deep learning in computer vision and language
understanding, research in recommendation has shifted to inventing new recommender …

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

To address the long-standing data sparsity problem in recommender systems (RSs), cross-
domain recommendation (CDR) has been proposed to leverage the relatively richer …

Graph Neural Network (GNN) based recommender systems have been attracting more and
more attention in recent years due to their excellent performance in accuracy. Representing …

This paper studies the multi-modal recommendation problem, where the item multi-modality
information (eg, images and textual descriptions) is exploited to improve the …

Intrusion detection exerts a crucial influence on securing the IIoT driven by anomaly
detection approaches. Dissimilar with the static data, the intrusion detection data is in the …

The ever-increasing web application programming interfaces (APIs) in various service-
sharing communities (eg, ProgrammableWeb. com and Mashape. com) have enabled …

Federated recommender system (FRS), which enables many local devices to train a shared
model jointly without transmitting local raw data, has become a prevalent recommendation …

In location-based social networks (LBSNs), extensive user check-in data incorporating user
preferences for location is collected through Internet of Things devices, including cell …