Papers with THU-KEG
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. |