There is a new sorting algorithm a deterministic O(m log2/3 n)-time algorithm for single-source shortest paths (SSSP) on ...

Nvidia has expanded its support of NetworkX graph analytic algorithms in RAPIDS, its open source library for accelerated computing. The expansion means data scientists can run 40-plus NetworkX ...

Dr. Alin Deutsch of UC San Diego explains in a Q&A why graph database algorithms will become the driving force behind the next generation of AI and machine learning apps.

The graph database is popular with social networks, but there's no reason to limit it to tracking people and their friendships.

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 ...

Graph Algorithms: Computational procedures designed to solve problems related to graph structures, encompassing processes such as traversal, shortest path determination, and network flow analysis.

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

That gives graph databases a leg up for applications such as fraud detection and recommendation systems. One of the major draws of graph databases is the ability to run graph computational algorithms.

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.