A super geeky topic, which could have super important repercussions in the real world. That description could very well fit anything from cold fusion to knowledge graphs, so a bit of unpacking is in ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

Heterogeneous graphs organize data with nodes and edges, and have been widely used in various graph-centric applications.

Entity alignment is a critical process for unifying heterogeneous data sources by identifying and linking entities that refer to the same real-world object across different knowledge graphs. This ...

Researchers around the world have a new way to apply big data to their work. Microsoft Research has released the Microsoft Academic Graph (MAG), a way to quickly assess and evaluate research papers, ...

Commuting graphs have emerged as a powerful framework for elucidating complex relationships within finite group theory. In these graphs, vertices typically represent non-central elements of a group, ...

Like all epidemics, the COVID-19 pandemic escalates in a crisis of individual and collective character. While in some ways crises bring people together, they also expose and stress systemic flaws and ...

SM-GNN prunes multi-view GNNs to pure propagation, cutting training time while outperforming prior MKGC accuracies on two ...

Graph databases are the fastest growing category in all of data management, according to DB-Engines.com, a database consultancy. Since seeing early adoption by companies including Twitter, Facebook ...

Uncover the hidden insights of your data with Graph Database Market. VANCOUVER, Canada - April 24, 2023 — Global Graph Database Market Size reached USD 1.59 Billion in 2020 and is expected to register ...