Graph optimisation problems encompass a diverse range of challenges aimed at finding optimal or near‐optimal solutions in networks or graphs. These problems are pivotal in areas such as ...

Graph cover problems form a critical area within discrete optimisation and theoretical computer science, addressing the challenge of selecting subsets of vertices (or edges) that satisfy ...

Identity management for cybersecurity is inherently a complex graph problem due to the vast, dynamic, and interconnected nature of modern IT environments.

Neo4j also trumpeted the value of graphs as vector databases used in generative artificial intelligence. AI training requires ...

We will apply these methods in two high-impact applications: long-read RNA transcript discovery, and indexing massive and rapidly growing genomic databases. This project paves the way for exact graph ...

Nvidia has expanded its support of NetworkX graph analytic algorithms in RAPIDS, its open source library for accelerated computing. The expansion means data scientists can run 40-plus NetworkX ...

Graph processing at hyperscale has historically been a challenge because of the sheer complexity of algorithms and graph workflows. Alibaba has been tackling this issue via a project called GraphScope ...

The State of Graph Databases Worldwide A few days ago, IBM released "The State of Graph Databases Worldwide," a report on the adoption and use case characteristics of graph databases.

You can think of a graph database as a set of interconnected circles (nodes) and each node represents a person, a product, a place or ‘thing’ that we want to build into our data universe.