While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...

Bringing knowledge graph and machine learning technology together can improve the accuracy of the outcomes and augment the potential of machine learning approaches. With knowledge graphs, AI language ...

A knowledge graph, is a graph that depicts the relationship between real-world entities, such as objects, events, situations, and concepts. This information is typically stored in a graph database and ...

"This is what we need to do. It's not popular right now, but this is why the stuff that is popular isn't working." That's a gross oversimplification of what scientist, best-selling author, and ...

Knowledge graphs are hyped. We can officially say this now, since Gartner included knowledge graphs in the 2018 hype cycle for emerging technologies. Though we did not have to wait for Gartner -- ...

What if you could transform overwhelming, disconnected datasets into a living, breathing map of relationships, one that not only organizes your data but also reveals insights you didn’t even know you ...

Graph database developer Neo4j Inc. is upping its machine learning game today with a new release of Neo4j for Graph Data Science framework that leverages deep learning and graph convolutional neural ...

Debate and discussion around data management, analytics, BI and information governance. This is a guest blogpost by Jim Webber, Chief Scientist at graph database provider Neo4j. It discusses Knowledge ...

When we ask Siri, Alexa or Google Home a question, we often get alarmingly relevant answers. Why? And more importantly, why don’t we get the same quality of answers and smooth experience in our ...