Entity Alignment
Leaderboards
Greatest papers with code
Jointly Learning Entity and Relation Representations for Entity Alignment
IJCNLP 2019
• THU-KEG/Entity_Alignment_Papers
• 
Entity alignment is a viable means for integrating heterogeneous knowledge among different knowledge graphs (KGs).
Multi-view Knowledge Graph Embedding for Entity Alignment
• THU-KEG/Entity_Alignment_Papers
•
Furthermore, we design some cross-KG inference methods to enhance the alignment between two KGs.
Recurrent Skipping Networks for Entity Alignment
• THU-KEG/Entity_Alignment_Papers
•
We consider the problem of learning knowledge graph (KG) embeddings for entity alignment (EA).
Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs
• nju-websoft/RSN
•
Moreover, triple-level learning is insufficient for the propagation of semantic information among entities, especially for the case of cross-KG embedding.
Deep Graph Matching Consensus
• rusty1s/deep-graph-matching-consensus
• 
This work presents a two-stage neural architecture for learning and refining structural correspondences between graphs.
Cross-lingual Entity Alignment via Joint Attribute-Preserving Embedding
• nju-websoft/JAPE
•
Our experimental results on real-world datasets show that this approach significantly outperforms the state-of-the-art embedding approaches for cross-lingual entity alignment and could be complemented with methods based on machine translation.
A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs
This study surveys 23 recent embedding-based entity alignment approaches and categorizes them based on their techniques and characteristics.
Multi-Channel Graph Neural Network for Entity Alignment
ACL 2019
• thunlp/MuGNN
•
Entity alignment typically suffers from the issues of structural heterogeneity and limited seed alignments.
Semi-supervised Entity Alignment via Joint Knowledge Embedding Model and Cross-graph Model
Specifically, as for the knowledge embedding model, we utilize TransE to implicitly complete two KGs towards consistency and learn relational constraints between entities.
Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs
Entity alignment is the task of linking entities with the same real-world identity from different knowledge graphs (KGs), which has been recently dominated by embedding-based methods.