274 citations · 579 across the 35 of their papers we have counts for
10 papers · 1 filter
EventEA: Benchmarking Entity Alignment for Event-centric Knowledge Graphs
Xiaobin Tian, Zequn Sun, Guangyao Li +1
Entity alignment is to find identical entities in different knowledge graphs (KGs) that refer to the same real-world object. Embedding-based entity alignment techniques have been d…
Lifelong Embedding Learning and Transfer for Growing Knowledge Graphs
Yuanning Cui, Yuxin Wang, Zequn Sun +4
Existing knowledge graph (KG) embedding models have primarily focused on static KGs. However, real-world KGs do not remain static, but rather evolve and grow in tandem with the dev…
Inductive Knowledge Graph Reasoning for Multi-batch Emerging Entities
Yuanning Cui, Yuxin Wang, Zequn Sun +4
Over the years, reasoning over knowledge graphs (KGs), which aims to infer new conclusions from known facts, has mostly focused on static KGs. The unceasing growth of knowledge in…
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…
: A Library for Multi-source Knowledge Graph Embeddings and Applications
Xindi Luo, Zequn Sun, Wei Hu
This paper presents , an open-source Python library for representation learning over knowledge graphs. supports joint representation learning over multi-so…
Facing Changes: Continual Entity Alignment for Growing Knowledge Graphs
Yuxin Wang, Yuanning Cui, Wenqiang Liu +4
Entity alignment is a basic and vital technique in knowledge graph (KG) integration. Over the years, research on entity alignment has resided on the assumption that KGs are static,…