Graph sparsification refers to the process of approximating a dense graph by a much sparser one while retaining key structural and spectral properties. In the context of linear systems, and in ...

Graph matching encompasses a class of computational problems aimed at identifying a correspondence between the vertex sets of two graphs so as to maximise structural similarity or alignment. Exact ...

LONDON--(BUSINESS WIRE)--Today Memgraph, the streaming graph application platform, announced Memgraph 2.0, the public launch of its source-available platform, making it easy for modern application ...

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 ...

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 ...

In algorithms, as in life, negativity can be a drag. Consider the problem of finding the shortest path between two points on a graph — a network of nodes connected by links, or edges. Often, these ...

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 ...

Like the core algorithm, Google’s Knowledge Graph periodically updates. But little has been known about how, when, and what it means — until now. I believe these updates consist of three things: ...

Whether you’re genuinely interested in getting insights and solving problems using data, or just attracted by what has been called “the most promising career” by LinkedIn and the “best job in America” ...