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

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.

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.

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

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

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 ...

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

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.

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.