Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion

Volume: 34, Issue: 05, Pages: 9612 - 9619
Published: Apr 3, 2020
Abstract
The rapid proliferation of knowledge graphs (KGs) has changed the paradigm for various AI-related applications. Despite their large sizes, modern KGs are far from complete and comprehensive. This has motivated the research in knowledge graph completion (KGC), which aims to infer missing values in incomplete knowledge triples. However, most existing KGC models treat the triples in KGs independently without leveraging the inherent and valuable...
Paper Details
Title
Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion
Published Date
Apr 3, 2020
Volume
34
Issue
05
Pages
9612 - 9619
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