LargeEA: Aligning Entities for Large-scale Knowledge Graphs

Summary: LargeEA scales entity alignment to massive KGs with two channels: structure via METIS-CPS mini-batch partitioning enabling batch-local learning for any EA method, and name via NFF with seedless augmentation. It fuses structure and name features; DBP1M provides a large-scale EA benchmark. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12730
Venue: VLDB
Year: 2022
Pagerank: 6.2534656e-05
Overall Rank: 4,354 | 69.75%
DOI: 10.14778/3489496.3489504

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,435	Real-time Workload Pattern Analysis for Large-scale Cloud Databases	2023	VLDB	7.0946114e-05
7,087	HongTu: Scalable Full-Graph GNN Training on Multiple GPUs	2023	SIGMOD	4.8324242e-05
8,910	Deep Active Alignment of Knowledge Graph Entities and Schemata	2023	SIGMOD	4.4229886e-05
8,913	PromptEM: Prompt-tuning for Low-resource Generalized Entity Matching	2023	VLDB	4.4229886e-05
10,579	NeutronTask: Scalable and Efficient Multi-GPU GNN Training with Task Parallelism	2025	VLDB	4.1905499e-05
11,018	ZeroEA: A Zero-Training Entity Alignment Framework via Pre-Trained Language Model	2024	VLDB	4.1905499e-05
11,036	TIGER: Training Inductive Graph Neural Network for Large-scale Knowledge Graph Reasoning	2024	VLDB	4.1905499e-05

Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
219	Deep Entity Matching with Pre-Trained Language Models	2021	VLDB	0.00033354456
293	Deep Learning for Entity Matching: A Design Space Exploration	2018	SIGMOD	0.00028661817
805	YAGO3: A Knowledge Base from Multilingual Wikipedias	2015	CIDR	0.00016431373
1,628	PARIS: Probabilistic Alignment of Relations, Instances, and Schema	2012	VLDB	0.00011074773
3,917	A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs	2020	VLDB	6.6268463e-05

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