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 ...

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 ...

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 ...

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 ...