Graphs are everywhere. In discrete mathematics, they are structures that show the connections between points, much like a ...

Back in the hazy olden days of the pre-2000s, navigating between two locations generally required someone to whip out a paper map and painstakingly figure out the most optimal route between those ...

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 ...

Graph algorithms constitute a fundamental area of computational research that focuses on the analysis and manipulation of graph structures, which represent systems of interconnected entities. In ...

One of the most classic algorithmic problems deals with calculating the shortest path between two points. A more complicated variant of the problem is when the route traverses a changing ...

Motif-based graph local clustering is a popular method for graph mining tasks due to its various applications, such as community detection, network optimization and graph learning. However, the ...

CATALOG DESCRIPTION: Design and analysis of advanced algorithms: graph algorithms; maximal network flows; min-cost flow algorithms; convex cost flows. REQUIRED TEXT ...

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 ...

Quantum computers promise to speed calculations dramatically in some key areas such as computational chemistry and high-speed networking. But they're so different from today's computers that ...

Abstract: The speed of algorithms on massive graphs depends on the size of the given data. Grammar-based compression is a technique to compress the size of a graph while still allowing to read or to ...