24 citations · 45 across the 15 of their papers we have counts for
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cs.LG2023★ 1 cited
What Makes Entities Similar? A Similarity Flooding Perspective for Multi-sourced Knowledge Graph Embeddings
Zequn Sun, Jiacheng Huang, Xiaozhou Xu +3
Joint representation learning over multi-sourced knowledge graphs (KGs) yields transferable and expressive embeddings that improve downstream tasks. Entity alignment (EA) is a crit…
cs.LG2023★ 1 cited
Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearning
Xiangrong Zhu, Guangyao Li, Wei Hu
Federated Learning (FL) recently emerges as a paradigm to train a global machine learning model across distributed clients without sharing raw data. Knowledge Graph (KG) embedding…
cs.LG2022★ 24 cited
Large-scale Entity Alignment via Knowledge Graph Merging, Partitioning and Embedding
Kexuan Xin, Zequn Sun, Wen Hua +3
Entity alignment is a crucial task in knowledge graph fusion. However, most entity alignment approaches have the scalability problem. Recent methods address this issue by dividing…