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 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 ...

In recent years, knowledge graphs have become an important tool for organizing and accessing large volumes of enterprise data in diverse industries — from healthcare to industrial, to banking and ...

Graph theory isn’t enough. The mathematical language for talking about connections, which usually depends on networks — vertices (dots) and edges (lines connecting them) — has been an invaluable way ...

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 ...

Polyglot persistence is becoming the norm in big data. Gone are the days when relational databases were the one store to rule them all; now the notion of using stores with data models that best align ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More This post is by Dr. Mukta Paliwal, senior data scientist at Persistent ...

This may come as a shock if you've first encountered knowledge graphs in Gartner's hype cycles and trends, or in the extensive coverage they are getting lately. But here it is: Knowledge graph ...