Identity management for cybersecurity is inherently a complex graph problem due to the vast, dynamic, and interconnected nature of modern IT environments. The Fast Company Executive Board is a private ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

The foundation for Knowledge Graphs and AI lies in the facets of semantic technology provided by AllegroGraph and Allegro CL. AllegroGraph is a graph based platform that enables businesses to extract ...

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...

Text mining and knowledge graphs connect cell-culture parameters to glycosylation for faster bioprocess optimization.

Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

PORTLAND, Ore.--(BUSINESS WIRE)--thatDot, Inc., a pioneer in complex event stream processing software, today released Quine. Quine’s unique approach combines graph data and streaming technologies into ...

LAFAYETTE, Calif., Feb. 8, 2021 — Franz Inc., an Artificial Intelligence (AI) innovator and leading supplier of Graph Database technology for AI Knowledge Graph Solutions, today announced AllegroGraph ...