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LLM-Matcher: A Name-Based Schema Matching Tool using Large Language Models

Summary: LLM-Matcher uses LLMs for name-only schema matching, yielding an interactive, interpretable initial mapping without instance data. Domain-aware feedback refines mappings to correct misconceptions, with experiments validating effectiveness in restricted settings. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h2a00ccff1259e384
Venue
SIGMOD
Year
2025
Pagerank
5.4535721e-05
Overall Rank
7,781 | 47.69%
DOI
10.1145/3722212.3725112

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{parciak_sigmod25,
        title = {{LLM-Matcher: A Name-Based Schema Matching Tool using Large Language Models}},
        author = {Parciak, Marcel and Vandevoort, Brecht and Neven, Frank and Peeters, Liesbet M. and Vansummeren, Stijn},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3722212.3725112},
        url = {https://dl.acm.org/doi/10.1145/3722212.3725112},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,837 EcoTable: Cost-effective Table Integration in Data Lakes for Natural Language Queries 2026 VLDB 4.9793485e-05
11,031 Interoperability in Healthcare: A Primer and New Frontiers 2026 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
134 Deep Entity Matching with Pre-Trained Language Models 2021 VLDB 0.00030043481
329 Can Foundation Models Wrangle Your Data? 2023 VLDB 0.00020858443
1,505 Generic Schema Matching, Ten Years Later 2011 VLDB 0.00010454635
Previous Page 1 / 1 Next

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