Contents
Be it a support technician who needs to solve a problem on site or an employee who needs further training on a specific topic. These are just two examples where it is important to provide the right content in the right context and at the right granularity. The status quo is usually that the right content is highly distributed, unstructured and not connected at all, and what you get to solve a problem, for example, is just a list of documents.
Applying knowledge graphs to content makes it possible to create intelligent content graphs that provide content as a service. This offers new possibilities for tailoring content to different information needs and making it available in the right way depending on the context.
We firmly believe that knowledge graphs combined with LLMs are the key to transparent and accurate content delivery. This combination enables the creation of AI solutions that users can trust.
Takeaways
The session focuses on
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How to turn content into an intelligent content graph
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What role taxonomies and ontologies play in this
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How LLMs can be integrated into this approach
Prior knowledge
Basic knowledge of iiRDS, taxonomies