Knowledge graph completion belongs to the category of Artificial Intelligence and Big Data and Smart Data. <\/p>\n
A knowledge graph is a large, interconnected database where a lot of information is logically linked \u2013 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.<\/p>\n
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.<\/p>\n
Thanks to knowledge graph completion, users can navigate large datasets more easily, receive more relevant search results, and benefit from more precise recommendations \u2013 for example, with digital assistants or in modern knowledge management systems.<\/p>","protected":false},"excerpt":{"rendered":"