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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 ...
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.
Provides many innovative ways to explore scientific papers, conferences, journals, and authors [104] Free Microsoft: Microsoft Academic Knowledge Graph: Multidisciplinary Provides an RDF data set about scientific publications and related entities, such as authors, institutions, journals, and fields of study.
1 Examples and types of graphs. ... This is a list of graph theory topics, ... Knowledge representation. Conceptual graph; Mind map;
The Knowledge Graph was powered in part by Freebase. [7] In August 2014, New Scientist reported that Google had launched a Knowledge Vault project. [14] After publication, Google reached out to Search Engine Land to explain that Knowledge Vault was a research report, not an active Google service.
A knowledge as a service provider responds to knowledge requests from users through a centralised knowledge server, and provides an interface between users and data owners. [2] [3] KaaS is one of several cloud computing-dependent business models in which computer resources are sold on an on-demand and pay-as-you-use basis. [4]
A standard representation of the pyramid form of DIKW models, from 2007 and earlier. [1] [2]The DIKW pyramid, also known variously as the knowledge pyramid, knowledge hierarchy, information hierarchy, [1]: 163 DIKW hierarchy, wisdom hierarchy, data pyramid, and information pyramid, [citation needed] sometimes also stylized as a chain, [3]: 15 [4] refer to models of possible structural and ...
As the body of published research grows, more traditional ways of searching for papers will become less effective in narrowing down relevant papers to a particular topic. For example, text-based similarity can only go so far in selecting which papers are relevant to a topic, whereas the addition of citation graphs could make use of giving ...