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Synthesis Lectures on Data, Semantics, and Knowledge

Synthesis Lectures on Data, Semantics, and Knowledge

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Synthesis Lectures on Data, Semantics, and Knowledge

Paulheim, Heiko; Ristoski, Petar; Portisch, Jan

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.

Details

Published by: Springer

Publication Date: 2023-06-04

Format: Hardcover

ISBN-13: 9783031303869

DOI: 10.1007/978-3-031-30387-6

Dimensions: 240cm x168cm

Pages: 158

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