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 ...

During the Build 2017 Day 2 keynote in May, Microsoft execs repeatedly referenced Microsoft Graph, the successor to Office Graph, as the key enabler of next-generation computing scenarios. Graph (the ...

Building a dependable database management system is no easy task. You need to understand what the design trade-offs in the construction of a database management system are and also how those ...