KGEL: A novel end-to-end embedding learning framework for knowledge graph completion

Title
KGEL: A novel end-to-end embedding learning framework for knowledge graph completion
Authors
Keywords
Knowledge graph, Link prediction, Weighted graph convolutional network, Tensor train decomposition, Tensor factorization
Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 167, Issue -, Pages 114164
Publisher
Elsevier BV
Online
2020-10-28
DOI
10.1016/j.eswa.2020.114164

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