Articles liés à Embedding Knowledge Graphs With Rdf2vec
Synopsis
This book explains the ideas behind one of the most well-known methods for knowledge graph embedding of transformations to compute vector representations from a graph, known as RDF2vec. The authors describe its usage in practice, from reusing pre-trained knowledge graph embeddings to training tailored vectors for a knowledge graph at hand. They also demonstrate different extensions of RDF2vec and how they affect not only the downstream performance, but also the expressivity of the resulting vector representation, and analyze the resulting vector spaces and the semantic properties they encode.
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À propos de l?auteur
Heiko Paulheim is a computer scientist and a full professor for Data Science at the University of Mannheim. His group conducts various projects around knowledge graphs, yielding, among others, the public knowledge graphs WebIsALOD, CaLiGraph, and DBkWik. Moreover, his group is concerned with using knowledge graphs in machine learning, which has lead to the development of the widespread RDF2vec method for knowledge graph embeddings. In the recent past, Heiko Paulheim also leads projects which are concerned with ethical, societal, and legal aspects of AI, including KareKoKI, which deals with the impact of price-setting AIs on antitrust legislation, and the ReNewRS project on ethical news recommenders.
Petar Ristoski is an applied researcher at eBay in San Jose, CA.
Jan Portisch is a PhD student at the University of Mannheim in cooperation with SAP SE - Business Technology Platform - One Domain Model.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Embedding Knowledge Graphs with RDF2vec
Edité par
Springer International Publishing, 2023
ISBN 10 : 3031303865
ISBN 13 : 9783031303869
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Embedding Knowledge Graphs with RDF2vec
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Springer, Berlin|Springer International Publishing|Springer, 2023
ISBN 10 : 3031303865
ISBN 13 : 9783031303869
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book explains the ideas behind one of the most well-known methods for knowledge graph embedding of transformations to compute vector representations from a graph, known as RDF2vec. The authors describe its usage in practice, from reusing pre-trained. N° de réf. du vendeur 834045501
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Embedding Knowledge Graphs with RDF2vec
Edité par
Springer International Publishing, 2023
ISBN 10 : 3031303865
ISBN 13 : 9783031303869
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explains the ideas behind one of the most well-known methods for knowledge graph embedding of transformations to compute vector representations from a graph, known as RDF2vec. The authors describe its usage in practice, from reusing pre-trained knowledge graph embeddings to training tailored vectors for a knowledge graph at hand. They also demonstrate different extensions of RDF2vec and how they affect not only the downstream performance, but also the expressivity of the resulting vector representation, and analyze the resulting vector spaces and the semantic properties they encode. N° de réf. du vendeur 9783031303869
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Embedding Knowledge Graphs with RDF2vec
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Springer International Publishing Jun 2023, 2023
ISBN 10 : 3031303865
ISBN 13 : 9783031303869
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book explains the ideas behind one of the most well-known methods for knowledge graph embedding of transformations to compute vector representations from a graph, known as RDF2vec. The authors describe its usage in practice, from reusing pre-trained knowledge graph embeddings to training tailored vectors for a knowledge graph at hand. They also demonstrate different extensions of RDF2vec and how they affect not only the downstream performance, but also the expressivity of the resulting vector representation, and analyze the resulting vector spaces and the semantic properties they encode. 168 pp. Englisch. N° de réf. du vendeur 9783031303869
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Embedding Knowledge Graphs with RDF2vec
ISBN 10 : 3031303865
ISBN 13 : 9783031303869
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Buch. Etat : Neu. Neuware -This book explains the ideas behind one of the most well-known methods for knowledge graph embedding of transformations to compute vector representations from a graph, known as RDF2vec. The authors describe its usage in practice, from reusing pre-trained knowledge graph embeddings to training tailored vectors for a knowledge graph at hand. They also demonstrate different extensions of RDF2vec and how they affect not only the downstream performance, but also the expressivity of the resulting vector representation, and analyze the resulting vector spaces and the semantic properties they encode.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 168 pp. Englisch. N° de réf. du vendeur 9783031303869
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Embedding Knowledge Graphs with RDF2vec
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Embedding Knowledge Graphs with RDF2vec
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Embedding Knowledge Graphs with RDF2vec
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