About: Knowledge graph embedding

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In representation learning, knowledge graph embedding (KGE), also referred to as knowledge representation learning (KRL), or multi-relation learning, is a machine learning task of learning a low-dimensional representation of a knowledge graph's entities and relations while preserving their semantic meaning. Leveraging their embedded representation, knowledge graphs (KGs) can be used for various applications such as link prediction, , , clustering, and relation extraction.

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rdfs:label	Incorporamento del grafo di conoscenza (it) Knowledge graph embedding (en)
rdfs:comment	In representation learning, knowledge graph embedding (KGE), also referred to as knowledge representation learning (KRL), or multi-relation learning, is a machine learning task of learning a low-dimensional representation of a knowledge graph's entities and relations while preserving their semantic meaning. Leveraging their embedded representation, knowledge graphs (KGs) can be used for various applications such as link prediction, , , clustering, and relation extraction. (en) Nella disciplina dell'apprendimento delle relazioni, l'incorporamento del grafo di conoscenza, o knowledge graph embedding (KGE) in inglese, anche riferito con il nome di knowledge representation learning (KRL), o apprendimento multi relazionale è un campo dell'apprendimento automatico che si occupa di apprendere una rappresentazione a bassa dimensionalità delle entità e relazioni che costituiscono un grafo della conoscenza o anche detto knowledge graph, cercando di preservare il loro significato semantico. Sfruttando la rappresentazione incorporata del grafo della conoscenza è possibile usare questo tipo di informazione per varie applicazioni come la predizione di collegamenti, la classificazione delle triple, il riconoscimento di entità, il raggruppamento, e l'estrazione di relazioni. (it)
foaf:depiction
dcterms:subject	Graph algorithms Machine learning Knowledge graphs Information science
Wikipage page ID	67944487 (xsd:integer)
Wikipage revision ID	1114013093 (xsd:integer)
Link from a Wikipage to another Wikipage	Convolutional layer Benchmark (computing) Deep neural network Lie group One-to-many (data model) Ellipse Machine learning Cluster analysis Embedding Batch learning Mahalanobis distance Spherical Many-to-many Graph algorithms Machine learning Torus Training set Knowledge graphs Hadamard product (matrices) Link prediction Euler's identity Fourier transform Capsule neural network Graph embedding Knowledge base Data mining Knowledge graph Recurrent neural network Reinforcement learning Asymmetric relation Tensor Hyperplane Information science Tucker decomposition Inner product space Recommender system Canonical polyadic decomposition Statistical relational learning Semantics Euclidean distance Overfitting Word2vec Drug repurposing Vector sum Analogical Many-to-one relation Relation extraction Representation learning Hermitian product Complex vector space dbr:Entity_recognition dbr:File:TransE.pdf dbr:Triple_Classification
Link from a Wikipage to an external page	https://wordnet.princeton.edu/ https://ogb.stanford.edu https://github.com/Accenture/AmpliGraph https://github.com/Sujit-O/pykg2vec https://github.com/awslabs/dgl-ke https://github.com/mnick/scikit-kge https://github.com/pykeen/pykeen https://github.com/thunlp/Fast-TransX https://github.com/thunlp/OpenKE https://github.com/torchkge-team/torchkge https://github.com/tranhungnghiep/MEI-KGE%7CMEI-KGE https://github.com/tranhungnghiep/MEIM-KGE%7CMEIM-KGE https://github.com/uma-pi1/kge
sameAs	Knowledge graph embedding Knowledge graph embedding Knowledge graph embedding
dbp:wikiPageUsesTemplate	dbt:GitHub dbt:Short_description dbt:Scholia
thumbnail	wiki-commons:Special:FilePath/KnowledgeGraphEmbedding.png?width=300
has abstract	In representation learning, knowledge graph embedding (KGE), also referred to as knowledge representation learning (KRL), or multi-relation learning, is a machine learning task of learning a low-dimensional representation of a knowledge graph's entities and relations while preserving their semantic meaning. Leveraging their embedded representation, knowledge graphs (KGs) can be used for various applications such as link prediction, , , clustering, and relation extraction. (en) Nella disciplina dell'apprendimento delle relazioni, l'incorporamento del grafo di conoscenza, o knowledge graph embedding (KGE) in inglese, anche riferito con il nome di knowledge representation learning (KRL), o apprendimento multi relazionale è un campo dell'apprendimento automatico che si occupa di apprendere una rappresentazione a bassa dimensionalità delle entità e relazioni che costituiscono un grafo della conoscenza o anche detto knowledge graph, cercando di preservare il loro significato semantico. Sfruttando la rappresentazione incorporata del grafo della conoscenza è possibile usare questo tipo di informazione per varie applicazioni come la predizione di collegamenti, la classificazione delle triple, il riconoscimento di entità, il raggruppamento, e l'estrazione di relazioni. Incorporamento di un grafo della conoscenza. Il vettore che rappresenta le entità e le relazioni può essere usato per differenti applicazioni nel campo dell'apprendimento automatico. (it)
prov:wasDerivedFrom	wikipedia-en:Knowledge_graph_embedding?oldid=1114013093&ns=0
page length (characters) of wiki page	53431 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:Knowledge_graph_embedding
is Link from a Wikipage to another Wikipage of	Machine learning Knowledge graph Statistical relational learning
is foaf:primaryTopic of	wikipedia-en:Knowledge_graph_embedding

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