Knowledge graph completion (glossary)

Knowledge graph completion belongs to the category of artificial intelligence, big data and smart data.

A knowledge graph is a large, networked database in which a lot of information is logically linked together - similar to a digital reference book that stores terms and their relationships. Knowledge graph completion describes the process by which gaps in such a knowledge network are automatically filled with new, suitable 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 describing which employees in your company have worked on certain projects. If a connection is missing, for example between an employee and a project, which should actually exist according to other data, the knowledge graph completion can detect this relationship and add it automatically. This ensures that your company knowledge is always up-to-date and complete.

Thanks to knowledge graph completion, users can find their way through large amounts of data more easily, receive more relevant search results and benefit from more precise recommendations - for example in digital assistants or in modern knowledge management systems.