Enriching Relations with Additional Attributes for ER
Summary: Defines relation enrichment: select a few KG-derived attributes to augment a relation's schema to maximize entity-resolution accuracy; problem is intractable. Uses tuple–KG linking and a reinforcement-learning policy jointly trained with ER to extract diverse, low-null attributes incrementally, yielding up to 33% ER gain. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Mengyi Yan (Beihang University)
- 2. Wenfei Fan (Beihang University; Shenzhen University; University of Edinburgh)
- 3. Yaoshu Wang (Shenzhen University)
- 4. Min Xie (Shenzhen University)
BibTeX Citation
@article{yan_vldb24,
title = {{Enriching Relations with Additional Attributes for ER}},
author = {Yan, Mengyi and Fan, Wenfei and Wang, Yaoshu and Xie, Min},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {11},
pages = {3109--3123},
doi = {10.14778/3681954.3681987},
url = {https://doi.org/10.14778/3681954.3681987},
year = {2024}
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