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RECA: Related Tables Enhanced Column Semantic Type Annotation Framework

Summary: RECA annotates column semantic types by aligning schema-similar, topic-relevant tables via a novel named-entity schema. Its architecture naturally scales to wide tables while exploiting inter-table context, substantially outperforming prior methods on web-table benchmarks. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
13185
Venue
VLDB
Year
2023
Pagerank
5.4217059e-05
Overall Rank
8,458 | 41.98%
DOI
10.14778/3583140.3583149

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{sun_vldb23,
        title = {{RECA: Related Tables Enhanced Column Semantic Type Annotation Framework}},
        author = {Sun, Yushi and Xin, Hao and Chen, Lei},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {6},
        pages = {1319--1331},
        doi = {10.14778/3583140.3583149},
        url = {https://doi.org/10.14778/3583140.3583149},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

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

Rank Cited Paper Year Venue Pagerank
94 Potter's Wheel: An Interactive Data Cleaning System 2001 VLDB 0.00034616103
397 TURL: Table Understanding through Representation Learning 2021 VLDB 0.00019278189
753 Recovering Semantics of Tables on the Web 2011 VLDB 0.00014336094
1,923 Annotating Columns with Pre-trained Language Models 2022 SIGMOD 9.4789109e-05
2,216 Open Data Integration 2018 VLDB 8.9374127e-05
2,223 Sato: Contextual Semantic Type Detection in Tables 2020 VLDB 8.9189986e-05
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