![]() ![]() 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. Schneider, in a discussion of how to build modular instructional systems for courses. The term was coined as early as 1972 by the Austrian linguist Edgar W. They are also prominently associated with and used by search engines such as Google, Bing, Yext and Yahoo knowledge-engines and question-answering services such as WolframAlpha, Apple's Siri, and Amazon Alexa and social networks such as LinkedIn and Facebook. Since the development of the Semantic Web, knowledge graphs are often associated with linked open data projects, focusing on the connections between concepts and entities. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the semantics underlying the used terminology. In knowledge representation and reasoning, knowledge graph is a knowledge base that uses a graph-structured data model or topology to integrate data. ![]()
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