Embedding Knowledge Graphs with RDF2vec (Record no. 86261)

000 -LEADER
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
-- PDF
-- 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

No items available.