A research team from the Songshan Lake Materials Laboratory has developed an AI-guided "Recommendation System" to discover ...

Graph machine learning (or graph model), represented by graph neural networks, employs machine learning (especially deep learning) to graph data and is an important research direction in the ...

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 ...

Debate and discussion around data management, analytics, BI and information governance. This is a guest blogpost by Neo4j’s Jim Webber, who says graphs are a way of managing complexity that is all ...

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 processing at hyperscale has historically been a challenge because of the sheer complexity of algorithms and graph workflows. Alibaba has been tackling this issue via a project called GraphScope ...

Imagimob Studio’s Graph UX update enhances user-friendliness and brings a collection of new capabilities to the ML design process. Machine learning (ML) and its benefits to a product's software suite ...