VersaMatch: Ontology Matching with Weak Supervision
Summary: VersaMatch: a weakly-supervised ontology matcher that synthesizes labels from heuristics, pattern rules, and external KBs to train discriminative models without manual annotation. At prediction it ensembles weak sources with the discriminator, improving F1 ≈+4pts vs weak‑supervision baselines and ≈+9pts on recent in‑the‑wild datasets. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Jonathan Fürst (NEC Corporation; Zurich University of Applied Sciences)
- 2. Mauricio Fadel Argerich (NEC Corporation; Universidad Politécnica de Madrid)
- 3. Bin Cheng (NEC Corporation; Springer Nature)
BibTeX Citation
@article{furst_vldb23,
title = {{VersaMatch: Ontology Matching with Weak Supervision}},
author = {Fürst, Jonathan and Argerich, Mauricio Fadel and Cheng, Bin},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {6},
pages = {1305--1318},
doi = {10.14778/3583140.3583148},
url = {https://doi.org/10.14778/3583140.3583148},
year = {2023}
}
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