Knowledge graph
A knowledge graph is a collection of interlinked descriptions of entities — real-world objects, events, situations or abstract concepts. It may include large volumes of factual information with semantics less formal than a traditional ontology. In some contexts, the term may refer to any knowledge base that is represented as a graph.
Knowledge graphs are often defined in association with Semantic Web technologies, linked data, large-scale data analytics and cloud computing to describe representations of knowledge that focus on the connections between concepts and entities.[1]
History
In the late 1980s, Groningen and Twente universities, jointly bega a project calnled Knowledge Graphs, which are semantic networks but with the added constraint that edges are restricted to be from a limited set of possible relations, to facilitate algebras on the graph. In the subsequent decades, the distinction between semantic networks and knowledge graphs was blurred.
Google introduced their Knowledge Graph[2] in 2012 by leveraging existing knowledge graphs, such as DBpedia and Freebase. They opened up the process for contributing to the graph by incorporationg RDFa and microdata formats from indexed web pages, which are based on vocabularies published by schema.org. [3] Through the success of Google Knowledge Graph and its use of semantic technologies the use of the term has been resurrected in semantic research to describe related projects.[3]
Definitions
There is no single commonly accepted definition of a knowledge graph. Popular definitions include:
- "A knowledge graph acquires and integrates information into an ontology and applies a reasoner to derive new knowledge." [1]
- "A knowledge graph (i) mainly describes real world entities and their interrelations, organized in a graph, (ii) defines possible classes and relations of entities in a schema, (iii) allows for potentially interrelating arbitrary entities with each other and (iv) covers various topical domains."[4]
- Knowledge graphs are large networks of entities, their semantic types, properties, and relationships between entities."[5]
Implementations
In 2012, Google introduced their Knowledge Graph as a semantic enhancement of Google’s search function that does not match strings, but enables searching for real-world objects. Since 2012, the term knowledge graph is also used to describe a family of applications. Frequently mentioned implementations are DBPedia, YAGO, Freebase, Wikidata, Yahoo’s semantic search assistant tool Spark, Google’s Knowledge Vault, Microsoft’s Satori and Facebook’s entity graph. [1]
See also
References
- ^ a b c Ehrlinger, Lisa; Wöß, Wolfram (2016). Towards a Definition of Knowledge Graphs (pdf). SEMANTiCS2016. Leipzig: Joint Proceedings of the Posters and Demos Track of 12th International Conference on Semantic Systems - SEMANTiCS2016 and 1st International Workshop on Semantic Change & Evolving Semantics (SuCCESS16). pp. 13–16.
- ^ Singhal, Amit. "Introducing the Knowledge Graph: things, not strings". Official Google Blog. Retrieved 21 March 2017.
{{cite web}}: Cite has empty unknown parameter:|dead-url=(help) - ^ a b McCusker, James P.; McGuiness, Deborah L. "What is a Knowledge Graph?". www.authorea.com. Retrieved 21 March 2017.
{{cite web}}: Cite has empty unknown parameter:|dead-url=(help) - ^ Paulheim, Heiko (2017). "Knowledge Graph Refinement: A Survey of Approaches and Evaluation Methods" (PDF). Semantic Web Journal: 489–508. Retrieved 21 March 2017.
- ^ Kroetsch, Markus; Weikum, Gerhard. "Special Issue on Knowledge Graph". Journal of Web Semantics. Retrieved 21 March 2017.