Knowledge graph completion (Glossary)

Knowledge graph completion belongs to the category of Artificial Intelligence and Big Data and Smart Data.

A knowledge graph is a large, interconnected database where a lot of information is logically linked – similar to a digital reference book that stores terms and their relationships. Knowledge graph completion describes the process of automatically filling gaps in such a knowledge network with new, relevant information. Artificial intelligence analyses known connections and recognises where important data is missing or where new data can be usefully added.

Imagine a knowledge graph that describes which employees in your company have worked on specific projects. If a connection is missing, for instance, between an employee and a project, which should actually exist according to other data, knowledge graph completion can discover this relationship and automatically add it. This ensures that your company knowledge becomes increasingly up-to-date and complete.

Thanks to knowledge graph completion, users can navigate large datasets more easily, receive more relevant search results, and benefit from more precise recommendations – for example, with digital assistants or in modern knowledge management systems.