Knowledge Graph
Knowledge Graph is a collection of interlinked descriptions of concepts, entities, relationships and events.
- Snippet from Wikipedia: Knowledge graph
In knowledge representation and reasoning, knowledge graph is a knowledge base that uses a graph-structured data model or topology to integrate data. 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.
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. 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.
- Snippet from Wikipedia: Google Knowledge Graph
The Google Knowledge Graph is a knowledge base from which Google serves relevant information in an infobox beside its search results. This allows the user to see the answer in a glance, as an instant answer. The data is generated automatically from a variety of sources, covering places, people, businesses, and more.
The information covered by Google's Knowledge Graph grew quickly after launch, tripling its data size within seven months (covering 570 million entities and 18 billion facts). By mid-2016, Google reported that it held 70 billion facts and answered "roughly one-third" of the 100 billion monthly searches they handled. By March 2023, this had grown to 800 billion facts on 8 billion entities.
There is no official documentation of how the Google Knowledge Graph is implemented. According to Google, its information is retrieved from many sources, including the CIA World Factbook and Wikipedia. It is used to answer direct spoken questions in Google Assistant and Google Home voice queries. It has been criticized for providing answers with neither source attribution nor citations.