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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
12917
Venue
VLDB
Year
2022
Pagerank
6.7232199e-05
Overall Rank
4,402 | 69.80%
DOI
10.14778/3489496.3489504

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Authors

BibTeX Citation

@article{ge_vldb22,
        title = {{LargeEA: Aligning Entities for Large-scale Knowledge Graphs}},
        author = {Ge, Congcong and Liu, Xiaoze and Chen, Lu and Gao, Yunjun and Zheng, Baihua},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {2},
        pages = {237--245},
        doi = {10.14778/3489496.3489504},
        url = {https://doi.org/10.14778/3489496.3489504},
        year = {2022}
}

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