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 ...

AWS, Google, Neo4j, Oracle. These were just some of the vendors represented in the W3C workshop on web standardization for graph data, and what transcribed is bound to boost adoption of the ...

There is a third way to create advanced data-driven apps and that is to be inspired by products but assemble a solution that imitates a pattern shown by a product. This approach has significant ...

In recent years, knowledge graphs have become an important tool for organizing and accessing large volumes of enterprise data in diverse industries — from healthcare to industrial, to banking ...

Knowledge graphs help in organizing unstructured data in a way that information can easily be extracted where explicit relations between multiple entities help in the process.

Language agnostic document processing: Finding relations using statistics, machine learning, and graphs Would you like to be able to find related work regardless of domain or language, more ...