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Active Learning of GAV Schema Mappings

Summary: Introduces GAV-Learn, an active-learning algorithm that derives GAV schema mappings from examples and black-box membership/equivalence queries. Produces minimal-size, accurate mappings and empirically outperforms prior example-based approaches. (summarized by gpt-5.6-luna on Jul 26 2026)

Paper ID
1753
Venue
PODS
Year
2018
Pagerank
6.0637959e-05
Overall Rank
5,859 | 59.81%
DOI
10.1145/3196959.3196974

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{cate_pods18,
        address = {New York, NY, USA},
        series = {{PODS} '18},
        title = {{Active Learning of GAV Schema Mappings}},
        url = {https://dl.acm.org/doi/10.1145/3196959.3196974},
        doi = {10.1145/3196959.3196974},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Cate, Balder ten and Kolaitis, Phokion G. and Qian, Kun and Tan, Wang-Chiew},
        year = {2018}
}

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