Papers with knowledge-driven applications

1 papers
Semi-supervised Entity Alignment via Joint Knowledge Embedding Model and Cross-graph Model (D19-1)

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Challenge: Entity alignment aims at integrating complementary knowledge graphs (KGs) from different sources or languages.
Approach: They propose a semi-supervised entity alignment method by joint Knowledge Embedding model and Cross-Graph model to make better use of seed alignments to propagate over the entire graphs with KG-based constraints.
Outcome: The proposed method can make better use of seed alignments to propagate over entire graphs with KG-based constraints.

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