Example of a sub-graph constructed from the QIAGEN biomedical knowledge graph. In this knowledge graph representation, gene and gene product entities are aggregated at the ortholog cluster level.

What exactly are knowledge graphs, and what's with all the hype about them? Learning to tell apart hype from reality, defining different types of graphs, and picking the right tools and database ...

For example, here is a Knowledge Graph result that appears for online computer hardware and software retailer Newegg. The ideal result for them would be a branded Knowledge Graph result.

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

Data warehousing is good for static BI projects, but knowledge graphs must be able to power insights in real time, otherwise they simply won’t work for applications like real-time recommendations, ...

For example, when Google started using knowledge graphs to enable semantic search in 2012, other technology companies like Facebook and Microsoft realized their power and started implementing them.

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

How to use knowledge graphs to improve customer experience — digging into the healthcare example.

The evolution of web search engines offers an instructive example, showing how knowledge can be extracted from unstructured sources and refined over time into a structured, interconnected graph.

But how do knowledge graphs work in practice? Well, one of the best examples is its effect on SEO. How knowledge graphs work with SEO ...