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ADnEV: Cross-Domain Schema Matching using Deep Similarity Matrix Adjustment and Evaluation

Summary: ADnEV post-processes matcher-generated similarity matrices with deep models that iteratively adjust and evaluate correspondences. It improves difficult schema/ontology matching and transfers across domains without learning domain-specific terminology. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12239
Venue
VLDB
Year
2020
Pagerank
5.6443833e-05
Overall Rank
7,325 | 49.75%
DOI
10.14778/3397230.3397237

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{shraga_vldb20,
        title = {{ADnEV: Cross-Domain Schema Matching using Deep Similarity Matrix Adjustment and Evaluation}},
        author = {Shraga, Roee and Gal, Avigdor and Roitman, Haggai},
        journal = {PVLDB},
        series = {{VLDB} '20},
        volume = {13},
        number = {9},
        pages = {1401--1415},
        doi = {10.14778/3397230.3397237},
        url = {https://doi.org/10.14778/3397230.3397237},
        year = {2020}
}

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