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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 ...
A knowledge graph is a knowledge base that uses a graph-structured data model. Common applications are for gathering lightly-structured associations between topic-specific knowledge in a range of disciplines, which each have their own more detailed data shapes and schemas .
This page was last edited on 19 August 2023, at 22:34 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may ...
Knowledge panel data about Thomas Jefferson displayed on Google Search, as of January 2015. 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 ...
In representation learning, knowledge graph embedding (KGE), also referred to as knowledge representation learning (KRL), or multi-relation learning, [1] is a machine learning task of learning a low-dimensional representation of a knowledge graph's entities and relations while preserving their semantic meaning.
A knowledge graph is a knowledge base that uses a graph-structured data model. Knowledge Graph may also refer to: Google Knowledge Graph, a knowledge graph that powers the Google search engine and other services; Bing Knowledge Graph or Satori, used by the Bing search engine; LinkedIn Knowledge Graph (LKG), a knowledge base for LinkedIn
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Freebase was a large collaborative knowledge base consisting of data composed mainly by its community members. It was an online collection of structured data harvested from many sources, including individual, user-submitted wiki contributions.
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