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, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the free-form semantics or relationships underlying these entities.
Since the development of the Semantic Web, knowledge graphs have often been associated with linked open data projects, focusing on the connections between concepts and entities. They are also historically 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.
Recent developments in data science and machine learning, particularly in graph neural networks and representation learning and also in machine learning, have broadened the scope of knowledge graphs beyond their traditional use in search engines and recommender systems. They are increasingly used in scientific research, with notable applications in fields such as genomics, proteomics, and systems biology.
- 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 May 2020, this had grown to 500 billion facts on 5 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.