SEPAKE: a structure-enhanced and position-aware knowledge embedding framework for knowledge graph co...
SEPAKE: a structure-enhanced and position-aware knowledge embedding framework for knowledge graph completion
About this item
Full title
Author / Creator
Yu, Mei , Jiang, Tingxu , Yu, Jian , Zhao, Mankun , Guo, Jiujiang , Yang, Ming , Yu, Ruiguo and Li, Xuewei
Publisher
New York: Springer US
Journal title
Language
English
Formats
Publication information
Publisher
New York: Springer US
Subjects
More information
Scope and Contents
Contents
Knowledge Graphs (KGs) provide supportively structured knowledge and have been applied to various downstream applications. Given a large amount of incomplete knowledge in KGs, knowledge graph completion (KGC) is proposed to reason over known facts and infer the missing links. The previous graph embedding approaches learn graph structure (i.e., trip...
Alternative Titles
Full title
SEPAKE: a structure-enhanced and position-aware knowledge embedding framework for knowledge graph completion
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2879633093
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2879633093
Other Identifiers
ISSN
0924-669X
E-ISSN
1573-7497
DOI
10.1007/s10489-023-04723-0
