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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

A canonical problem in computer science is to find the shortest route to every point in a network. A new approach beats the ...

Graph database vendor Neo4j Inc. is teaming up with Snowflake Inc. to make a library of Neo4j’s graph analytics functions available in the Snowflake cloud. The deal announced today allows users to ...

Korean research institute Kaist has found a way to develop a one trillion edge graph algorithm on a single computer without storing the graph in the main memory or on disc. ‘Develop’ is the important ...

With Klout-like talent scores and Pandora-like recommendations for the job world, LinkedIn’s magical algorithm is combing copious amounts of data to help employers discover top talent. Imagine if your ...