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 ...

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 ...

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 ...

Scalable Graph Algorithms for Bioinformatics using Structure, Parameterization and Dynamic Updates, ERC Consolidator Grant, 9/2025-8/2030 Sequencing technologies have developed to be cheap and ...

Discover what context graphs are, why they're revolutionizing AI systems, and who's building this trillion-dollar technology ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now DeepMind wants to enable neural networks to ...

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 ...