This information is typically stored in a graph database and subsequently represented as a graph structure, which is the basis for the term "knowledge graph." History of Knowledge Graphs ...

Building knowledge graphs from your data One key feature of Neo4j is the concept of the knowledge graph, linking unstructured information in nodes into a structured graph.

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 ...

Graphs naturally generalize unstructured vectorial data and structured data such as time series, images or bags of entities. The goal of this course is to provide an overview of the fundamental ...

Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks.

Enterprise knowledge graphs’ representation of an organization’s content and data creates a model that integrates structured and unstructured data. Hilger and Nash described what a knowledge graph is, ...

Data-hungry AI applications are fed complex information, and that's where graph databases and knowledge graphs play a crucial role.