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Supervised Meta-blocking

Summary: Supervised meta-blocking learns classifiers to prune entity-resolution comparisons, beating coarse pruning. Compact feature set, low extraction cost, strong discrimination; effective with small training data; evaluated on 10 real/synthetic datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
he78cf8a7b0fe4901
Venue
VLDB
Year
2014
Pagerank
6.2906903e-05
Overall Rank
5,064 | 65.96%
DOI
10.14778/2733085.2733098

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{papadakis_vldb14,
        title = {{Supervised Meta-blocking}},
        author = {Papadakis, George and Papastefanatos, George and Koutrika, Georgia},
        journal = {PVLDB},
        series = {{VLDB} '14},
        volume = {7},
        number = {14},
        pages = {1929--1932},
        doi = {10.14778/2733085.2733098},
        url = {https://doi.org/10.14778/2733085.2733098},
        year = {2014}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

Rank Cited Paper Year Venue Pagerank
60 The Merge/Purge Problem for Large Databases 1995 SIGMOD 0.000394583
108 Approximate String Joins in a Database (Almost) for Free 2001 VLDB 0.0003305531
1,114 Principles of Dataspace Systems 2006 PODS 0.00011964697
1,307 Entity Resolution with Iterative Blocking 2009 SIGMOD 0.000110838
5,946 Exploiting Context Analysis for Combining Multiple Entity Resolution Systems 2009 SIGMOD 5.9379643e-05
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