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 ...

Part I of our series on graph analytics introduced us to graph analytics, and its brethren graph databases. We talked about the use of graph analytics to understand and visualize relationships between ...

Six years ago, Afonso Bandeira and Shuyang Ling were attempting to come up with a better way to discern clusters in enormous data sets when they stumbled into a surreal world. Ling realized that the ...

Imagine 100 dots scattered in front of you. In a haphazard variation on connect-the-dots, start drawing lines between the points. How many lines can you draw without producing a triangle? A square? An ...

The latest trends and issues around the use of open source software in the enterprise. As defined nicely here by Hitachi Vantara’s Bill Schmarzo, “Graph analytics leverage graph structures to ...

Creating a graph doesn’t need to be difficult once you have the right tools at your disposal. Now, instead of having to draw a graph on a piece of paper, or use advanced applications to get the job ...

What Is a Graph Database? Your email has been sent Explore the concept of graph databases, their use cases, benefits, drawbacks, and popular tools. A graph database is a dynamic database management ...