Knowledge graphs are real. They have been for the last 20 years at least. Knowledge graphs, in their original definition and incarnation, have been about knowledge representation and reasoning.

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

To stay visible in AI search, your content must be machine-readable. Schema markup and knowledge graphs help you define what ...

How knowledge graphs work with SEO Google’s Knowledge Graph was introduced in 2012 to provide more useful and relevant results to searches using semantic-search techniques.

Graph database vendors seem to verify this across the board: 2019 was a very good year. Having identified knowledge graphs as a key technology for the 2020s, we take a look at how they are evolving.

Knowledge graphs—machine-readable data representations that mimic human knowledge—are bridging the gap between proprietary enterprise data and safe, reliable, helpful LLMs.

Knowledge graphs also allow you to create structures for the relationships in the graph. You can tell a graph that parents have children and parents can be children and children can be brothers or ...

Cassie Shum, VP of Field Engineering at RelationalAI, joins host Keith Shaw on DEMO to showcase how enterprises can unlock ...

Knowledge graph-based recommender systems are able to help solve these challenges to an extent. In this approach, user and item entities are connected through multiple relationships.