BIOENGINEER

Dynamic Graph AI Model Hits Nearly 96% Accuracy in Traffic Congestion Prediction

A new dynamic graph neural framework called GAMMA-Traffic updates road-network connections in real time using ...
BIOENGINEER

Semantic-guided graph attention model improves cross-domain recommendation on Amazon data

A new semantic-guided graph attention framework improves rating prediction and ranking on Amazon cross-domain recommendation ...
ScienceBlog

How Graph Neural Networks Are Outsmarting Global Criminal Networks

Financial fraud has evolved into increasingly sophisticated networks of deception, with criminals exploiting complex webs of transactions to launder money and coordinate elaborate schemes. Traditional ...
EurekAlert!

A multi-view heterogeneous and extractive graph attention network for evidential document-level event factuality identification

Document-level Event Factuality Identification (DEFI) has always been the focus of Information Extraction and Information Credibility. This paper studies a novel task named Evidential Document-level ...
techtarget

What are graph neural networks (GNNs)?

Graph neural networks (GNNs) are a type of neural network architecture and deep learning method that can help users analyze graphs, enabling them to make predictions based on the data described by a ...