General structure: A network of entities, their semantic types, properties, and relationships.Flexible relations among knowledge in topical domains: A knowledge graph (i) defines abstract classes and relations of entities in a schema, (ii) mainly describes real world entities and their interrelations, organized in a graph, (iii) allows for potentially interrelating arbitrary entities with each other, and (iv) covers various topical domains.Most definitions view the topic through a Semantic Web lens and include these features: There is no single commonly accepted definition of a knowledge graph. In 2019, IEEE combined its annual international conferences on "Big Knowledge" and "Data Mining and Intelligent Computing" into the International Conference on Knowledge Graph. These include Facebook, LinkedIn, Airbnb, Microsoft, Amazon, Uber and eBay. Since then, several large multinationals have advertised their knowledge graphs use, further popularising the term. The Google Knowledge Graph became a successful complement to string-based search within Google, and its popularity online brought the term into more common use. Entity and relationship types associated with this knowledge graph have been further organized using terms from the vocabulary. They later incorporated RDFa, Microdata, JSON-LD content extracted from indexed web pages, including the CIA World Factbook, Wikidata, and Wikipedia. In 2012, Google introduced their Knowledge Graph, building on DBpedia and Freebase among other sources. Neither described themselves as a 'knowledge graph' but developed and described related concepts. DBpedia focused exclusively on data extracted from Wikipedia, while Freebase also included a range of public datasets.
In 2007, both DBpedia and Freebase were founded as graph-based knowledge repositories for general-purpose knowledge. In 1998 Andrew Edmonds of Science in Finance Ltd in the UK created a system called ThinkBase that offered fuzzy-logic based reasoning in a graphical context. In 2005, Marc Wirk founded Geonames to capture relationships between different geographic names and locales and associated entities. In 1985, Wordnet was founded, capturing semantic relationships between words and meanings – an application of this idea to language itself. Some early knowledge graphs were topic-specific. In subsequent decades, the distinction between semantic networks and knowledge graphs was blurred. In the late 1980s, University of Groningen and University of Twente jointly began a project called Knowledge Graphs, focusing on the design of semantic networks with edges restricted to a limited set of relations, to facilitate algebras on the graph.
The term was coined as early as 1972, in a discussion of how to build modular instructional systems for courses.