Mathematicians have long sought to develop algorithms that can compare any two graphs. In practice, many algorithms always seem to work efficiently. But in theory, there is no guarantee ...

Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.

If you were to look at it, Holm says, a “good” embedding would be simple, unconvoluted. The standard example is the so-called Ladder Graph. A balanced embedding of this graph looks exactly ...

Now Neo4j is hoping to drive that complexity from the equation with the general availability of Aura Data Science, it’s first cloud-based graph data science offering. It also is launching Graph Data ...

And sometimes simple-looking graphs actually make it harder to understand the data they are based on. Ira talks with Jeremy Wilmer, associate professor, and Sarah Horan Kerns, research associate, at ...

Elementary students in 10 city school systems struggled to perform simple investigations, interpret basic graphs and diagrams, and understand scientific classifications and relationships ...

Neo4j Graph Data Science makes it easy for data scientists to work within their existing data pipeline of tools across their ecosystem. Data scientists can use Neo4j Graph Data Science on-premises, ...

These graphs not only offer insights into the intrinsic algebraic properties of simple groups but also have applications in computational group theory, cryptography and network design.