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 ...

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 new open-source library by Nvidia could be the secret ingredient to advancing analytics and making graph databases faster. The key: parallel processing on Nvidia GPUs. Nvidia has long ago stopped ...

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 ...

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 ...

Reduced link graphs are a way that search engines can identify high quality websites and remove low quality spam sites from the link ranking calculation. Published research demonstrates that reduced ...