Embedding Knowledge Graphs with RDF2vec
Language: English
Published by Springer, Springer International Publishing Jun 2024, 2024
- Softcover
- New
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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This item is printed on demand - Print on Demand Titel. 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 KG, Sachsenplatz 4-6, 1201 Wien 168 pp. Englisch.
Seller Inventory # 9783031303890
- Title
- Embedding Knowledge Graphs with RDF2vec
- Author
- Heiko Paulheim
- Publisher
- Springer, Springer International Publishing Jun 2024
- Publication year
- 2024
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 303130389X
- ISBN 13
- 9783031303890
- Item weight
- 294 grams
- Dimensions
- 240x168x10 mm
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.
"Synopsis" may belong to another edition of this title.
About the Author
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.
"About the title" may belong to another edition of this title.
buchversandmimpf2000
Emtmannsberg, BAYE, Germany
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