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FusedGW Entity Alignment

This is a Python implementation of

A Fused Gromov-Wasserstein Framework for Unsupervised Knowledge Graph Entity Alignment

Jianheng Tang, Kangfei Zhao, Jia Li

ACL 2023 (Findings)

Dependencies

  • python 3.10.6
  • pytorch 1.13.0
  • SentenceTransformer 2.2.2
  • argparse 1.1
  • dgl 0.9.1

How to run

All datasets and pretrained embeddings used in the paper are on google drive. Download and unzip all files in the data folder.

Run bash run.sh to reproduce all the experimental results in our paper.

@inproceedings{FGWEA,
    title = "A Fused {G}romov-{W}asserstein Framework for Unsupervised Knowledge Graph Entity Alignment",
    author = "Tang, Jianheng  and
      Zhao, Kangfei  and
      Li, Jia",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
    url = "https://aclanthology.org/2023.findings-acl.205",
    doi = "10.18653/v1/2023.findings-acl.205",
    pages = "3320--3334",
}

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"A Fused Gromov-Wasserstein Framework for Unsupervised Knowledge Graph Entity Alignment" in ACL 2023 (Findings)

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