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 ...

Our research focuses on graphs and their multiple applications: from integrating graph databases to program comprehension or from finding subgraphs efficiently to the Web of Data.

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 ...

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

The recent increase in the popularity of property graph databases is well-founded, as they fulfill a real need. But as usage continues to ramp up, the limitations of traditional property graph systems ...

A graph database can help you discover connections in your data you never imagined; here’s how to get started Alaa Mahmoud is an advisory software engineer and master inventor at IBM Analytics Cloud ...

Showing developers how to build smarter apps is going to be one of the pillars of Microsoft's Build 2016 conference next week. At the heart of that lesson will be Microsoft Graph, the technology ...