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dual-amn's Introduction

Boosting the Speed of Entity Alignment10×: Dual AttentionMatching Network with Normalized Hard Sample Mining (https://arxiv.org/pdf/2103.15452.pdf)

Datasets

The datasets are from GCN-Align, JAPE, and RSNs.

  • ent_ids_1: ids for entities in source KG;
  • ent_ids_2: ids for entities in target KG;
  • ref_ent_ids: entity links encoded by ids;
  • triples_1: relation triples encoded by ids in source KG;
  • triples_2: relation triples encoded by ids in target KG;

Environment

  • Python = 3.6
  • Keras = 2.2.5
  • Tensorflow = 1.14.0
  • jupyter
  • Scipy
  • Numpy
  • tqdm
  • numba

Acknowledgement

We refer to the codes of these repos: keras-gat, GCN-Align. Thanks for their great contributions!

dual-amn's People

Contributors

maoxinn avatar

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