Graph algorithms and sparsification techniques have emerged as pivotal tools in the analysis and optimisation of complex networked systems. These approaches focus on reducing the number of edges in a ...

Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring. These methods ...

In recent years, the Massively Parallel Computation (MPC) model has gained significant attention. However, most of distributed and parallel graph algorithms in the MPC model are designed for static ...

Graphs are widely used to represent a wide variety of systems, ranging from the relationships between users of a social network to the payments among a network of bank accounts, and graph algorithms ...

A couple of weeks ago, I attended and spoke at the first stop in the Neo4j GraphTour in Washington D.C. and I was able to get the best answer yet to a question that I’d been pondering: what’s the ...

A puzzle that has long flummoxed computers and the scientists who program them has suddenly become far more manageable. A new algorithm efficiently solves the graph isomorphism problem, computer ...

Two computer scientists found — in the unlikeliest of places — just the idea they needed to make a big leap in graph theory. This past October, as Jacob Holm and Eva Rotenberg were thumbing through a ...

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, ...