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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
10889
Venue
VLDB
Year
2014
Pagerank
5.7903293e-05
Overall Rank
4,974 | 65.40%
DOI
-

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

Rank Cited Paper Year Venue Pagerank
67 The Merge/Purge Problem for Large Databases 1995 SIGMOD 0.00061348205
125 Approximate String Joins in a Database (Almost) for Free 2001 VLDB 0.00044847972
1,252 Principles of Dataspace Systems 2006 PODS 0.00013033186
1,410 Entity Resolution with Iterative Blocking 2009 SIGMOD 0.00012127555
5,798 Exploiting Context Analysis for Combining Multiple Entity Resolution Systems 2009 SIGMOD 5.3231654e-05
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