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Knowledge graph
open-in-new
<p>In <a href="/facts/Knowledge_representation_and_reasoning/9lnzyILD">knowledge representation and reasoning</a>, a knowledge graph is a <a href="/facts/Knowledge_base/zKXdqQjH">knowledge base</a> that uses a <a href="/facts/Graph_(discrete_mathematics)/kw3eIBUe">graph</a>-structured <a href="/facts/Data_model/j1YyzpJ3">data model</a> or <a href="/facts/Topology/2EqW47cU">topology</a> to represent and operate on <a href="/facts/Data/AUBFN97o">data</a>. Knowledge graphs are often used to store interlinked descriptions of <a href="/facts/Named_entity/pqC6pucA">entities</a> – objects, events, situations or abstract concepts – while also encoding the free-form <a href="/facts/Semantics/1L4WwLAP">semantics</a> or relationships underlying these entities. </p><p>Since the development of the <a href="/facts/Semantic_Web/NFHo9dB7">Semantic Web</a>, knowledge graphs have often been associated with <a href="/facts/Linked_data/XKhE5aTQ">linked open data</a> projects, focusing on the connections between <a href="/facts/Concept/VWB6yhQp">concepts</a> and entities. They are also historically associated with and used by <a href="/facts/Search_engine/SRntsbz2">search engines</a> such as <a href="/facts/Google_Knowledge_Graph/IgQEyHPp">Google</a>, <a href="/facts/Bing_(search_engine)/r2pIK5HT">Bing</a>, <a href="/facts/Yext/NBJNH6Hw">Yext</a> and <a href="/facts/Yahoo/nKhTaV3M">Yahoo</a>; <a href="/facts/Knowledge_Engine_(Wikimedia_Foundation)/B85BI0k4">knowledge-engines</a> and question-answering services such as <a href="/facts/WolframAlpha/CIBhWgXA">WolframAlpha</a>, Apple's <a href="/facts/Siri/wfkBV2dF">Siri</a>, and Amazon <a href="/facts/Amazon_Alexa/deexPRqM">Alexa</a>; and <a href="/facts/Social_network/kQg6aEVf">social networks</a> such as <a href="/facts/LinkedIn/Iq2IcNMt">LinkedIn</a> and <a href="/facts/Facebook/0IhXFR6u">Facebook</a>. </p><p>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. </p>