Well, one of the best examples is its effect on SEO. Google’s Knowledge Graph was introduced in 2012 to provide more useful and relevant results to searches using semantic-search techniques.

A knowledge graph combines entities of various types ... including relationship type, direction, effect, context and source. Causality of the relationships is represented through direction.

Unlike traditional databases, knowledge graphs organize information as nodes and edges, making them better for AI systems that reason & infer.

Ever since the introduction of the Google Knowledge Graph, a growing number of organizations have adopted this powerful technology to drive efficiency and effectiveness in their data management.

A knowledge graph is a collection of relationships between entities defined using a standardized vocabulary. It structures data in a meaningful way, enabling greater efficiencies and accuracies in ...

They require a knowledge graph. How does the journey to a knowledge graph start with unstructured data—such as text, images, and other media? The evolution of web search engines offers an ...

The Knowledge Graph appears to be based on a data-lake approach rather than the data-river approach of today’s core algorithm (delayed reaction versus immediate effect). However, the fact that ...