Graph algorithms and sparsification techniques have emerged as pivotal tools in the analysis and optimisation of complex networked systems.

Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring.

In an era where autonomous systems demand pinpoint accuracy, navigation algorithms face a tough trade-off between precision ...

Our research is focused on graph algorithms, from both a theoretical perspective, and a practical perspective motivated by real-world problems in Bioinformatics, such as genome sequencing technologies ...

Two computer scientists found — in the unlikeliest of places — just the idea they needed to make a big leap in graph theory.

It also compresses data up to 10 times. TigerGraph also supports different graph partitioning algorithms enabling it to split very large graphs over a distributed architecture.

Published research demonstrates that reduced link graphs are an effective way to rank links. This article discusses research and patents that explain how reduced link graph algorithms work.

Nov. 11, 2021 — TigerGraph, provider of the leading graph analytics platform, has announced its enhanced Graph Data Science Library (previously named the GSQL Graph Algorithm Library.) This latest ...

Graph analytics is a hot topic, but what does it mean? At the DC GraphTour, I learned the difference between graph queries, graph algorithms, and graph analytics. Next up: San Francisco GraphTour.

In July/August 2019, two things changed with Google's Knowledge Graph API that may be a turning point both for Google and for us as digital marketers.