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Deep Active Alignment of Knowledge Graph Entities and Schemata

Summary: DAAKG learns embeddings for entities, relations, and classes to align entities and schemata across KG pairs semi-supervisedly. Active learning guides batch labeling with approximation methods, yielding strong accuracy and generalization on benchmarks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6724
Venue
SIGMOD
Year
2023
Pagerank
5.3251649e-05
Overall Rank
9,063 | 37.83%
DOI
10.1145/3589304

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{huang_sigmod23,
        title = {{Deep Active Alignment of Knowledge Graph Entities and Schemata}},
        author = {Huang, Jiacheng and Sun, Zequn and Chen, Qijin and Xu, Xiaozhou and Ren, Weijun and Hu, Wei},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3589304},
        url = {https://dl.acm.org/doi/10.1145/3589304},
        year = {2023}
}

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