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Embedding Knowledge Graphs with RDF2vec

By (author) Heiko Paulheim, By (author) Petar Ristoski, By (author) Jan Portisch






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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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Normally shipped | Enquiries only
Publisher | Springer International Publishing AG
Published date | 4 Jun 2023
Language |
Format | Hardback
Pages | 158
Dimensions | 240 x 168 x 0mm (L x W x H)
Weight | 0g
ISBN | 978-3-0313-0386-9
Readership Age |
BISAC | computers / expert systems


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