Graph labeling is a central topic in combinatorial optimisation that involves assigning numerical or categorical labels to vertices or edges of a graph subject to specific constraints. This framework ...

Discover what context graphs are, why they're revolutionizing AI systems, and who's building this trillion-dollar technology ...

Forbes contributors publish independent expert analyses and insights. I write about blockchain and big data, primarily focusing on XRP. By applying a well-known graph algorithm to the XRP ledger data, ...

Graph algorithms and spanners have emerged as a critical area of research in computer science, underpinning both theoretical advances and practical applications such as network design, routing ...

It might not be as bright and shiny as some of the other topics that we've seen here, but there's no denying that the work of Julian Shun and his team is going to be applicable to a lot of the ...

I have a network of Tasks, that have precondition/postcondition relationships.<BR><BR>Googling around, I think that this Graph is a Directed Acyclic Graph, so I'm ...

Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of ...

Graph databases, which explicitly express the connections between nodes, are more efficient at the analysis of networks (computer, human, geographic, or otherwise) than relational databases. That ...

The problem: The app must store a collection of people and who they know. Sometimes it must find out everyone who knows someone who knows Bob. Sometimes it must look further for everyone who is three ...