Embedding Knowledge Graphs with RDF2vec
Buch in deiner Nähe kaufen
Beschreibung
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.
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.
Explains what are knowledge graph embeddings are and how they can be computed Demonstrates how RDF2vec is used as a building block in AI applications Discusses which variants of RDF2vec exist and when to use them
Autor*in
Heiko Paulheim
Themen in »Embedding Knowledge Graphs with RDF2vec«
Data mining knowledge representation in AI Knowledge Graph Embeddings dynamic knowledge graphs ontology learning