SAN MATEO, Calif., Oct. 20, 2020 — Neo4j, a leader in graph technology, announced that the majority of its customers are now deploying their graph applications in the cloud, facilitated by flexible ...

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 ...

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 ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...

Knowledge graphs and ontologies form the backbone of the Semantic Web by enabling the structured representation and interconnection of data across diverse domains. These frameworks allow for the ...

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 ...

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 ...

Physicists have long recognized the value of photonic graph states in quantum information processing. However, the difficulty ...