Embedding Knowledge Graphs with RDF2vec (Record no. 86261)
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000 -LEADER | |
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fixed length control field | 03096nam a22005535i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-031-30387-6 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20240730165337.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 230603s2023 sz | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783031303876 |
-- | 978-3-031-30387-6 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 006.3 |
100 1# - AUTHOR NAME | |
Author | Paulheim, Heiko. |
245 10 - TITLE STATEMENT | |
Title | Embedding Knowledge Graphs with RDF2vec |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2023. |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | IX, 158 p. 43 illus., 27 illus. in color. |
490 1# - SERIES STATEMENT | |
Series statement | Synthesis Lectures on Data, Semantics, and Knowledge, |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | Introduction -- From Word Embeddings to Knowledge Graph Embeddings -- RDF2vec Variants and Representations -- Tweaking RDF2vec -- RDF2vec at Scale -- Example Applications beyond Node Classification -- Link Prediction in Knowledge Graphs (and its Relation to RDF2vec) -- Future Directions for RDF2vec. |
520 ## - SUMMARY, ETC. | |
Summary, etc | 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. |
700 1# - AUTHOR 2 | |
Author 2 | Ristoski, Petar. |
700 1# - AUTHOR 2 | |
Author 2 | Portisch, Jan. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | https://doi.org/10.1007/978-3-031-30387-6 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks |
100 1# - AUTHOR NAME | |
-- | (orcid) |
-- | 0000-0003-4386-8195 |
264 #1 - | |
-- | Cham : |
-- | Springer International Publishing : |
-- | Imprint: Springer, |
-- | 2023. |
336 ## - | |
-- | text |
-- | txt |
-- | rdacontent |
337 ## - | |
-- | computer |
-- | c |
-- | rdamedia |
338 ## - | |
-- | online resource |
-- | cr |
-- | rdacarrier |
347 ## - | |
-- | text file |
-- | |
-- | rda |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial intelligence. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Data mining. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Expert systems (Computer science). |
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial Intelligence. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Data Mining and Knowledge Discovery. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Knowledge Based Systems. |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
-- | 2691-2031 |
912 ## - | |
-- | ZDB-2-SXSC |
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