Entities and Relations for representing individual pieces of data, and Types for adding structure to information.” Entities, Relations and Types are defined by developers. The Graph will release ...

Graphs are among the most widely-used data structures in machine learning. Their power comes from the flexibility of capturing relations (edges) of collections of entities (nodes) which arise in a ...

Enterprise knowledge graphs’ representation of an organization’s content and data creates a model that integrates structured ... They are powerful in helping to structure information across an ...

“We’ve realized that the data structures we’ve used to study things ... each co-authored by all three mathematicians (ABC). A graph representation of co-authorship, taken from either data set, might ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization ...

(For reference, according to Facebook engineers, the Social Graph is a graph data structure involving an "immense map" of people, places, and things and the connections between them.) Touted as a ...