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 ...

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 ...

Dijkstra's algorithm has long been the quickest way of finding the shortest possible paths in a network, but researchers have ...

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 ...

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 ...

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, ...

It hadn’t occurred to me in quite these terms before, but Google has an algorithm for its Knowledge Graph. I have been tracking the Knowledge Graph API for five years. The resultScores have always ...

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 ...