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BLAST: a Loosely Schema-aware Meta-blocking Approach for Entity Resolution

Summary: BLAST is a loosely schema-aware meta-blocking method for entity resolution using data-derived stats to improve blocks beyond schema-agnostic methods. LSH-based extraction scales to large data, delivering better coverage and beating unsupervised meta-blocking. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h09ae2e9afd9ade95
Venue
VLDB
Year
2016
Pagerank
7.0627813e-05
Overall Rank
3,738 | 74.87%
DOI
10.14778/2994509.2994533

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{simonini_vldb16,
        title = {{BLAST: a Loosely Schema-aware Meta-blocking Approach for Entity Resolution}},
        author = {Simonini, Giovanni and Bergamaschi, Sonia and Jagadish, H.V.},
        journal = {PVLDB},
        series = {{VLDB} '16},
        volume = {9},
        number = {12},
        pages = {1173--1184},
        doi = {10.14778/2994509.2994533},
        url = {https://doi.org/10.14778/2994509.2994533},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

Showing 9 of 9 citing papers.

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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
108 Approximate String Joins in a Database (Almost) for Free 2001 VLDB 0.0003305531
427 Big Data Integration 2013 VLDB 0.00018465558
991 Web-scale Data Integration: You can only afford to Pay As You Go 2007 CIDR 0.00012647155
5,064 Supervised Meta-blocking 2014 VLDB 6.2906903e-05
5,143 Schema-agnostic vs Schema-based Configurations for Blocking Methods on Homogeneous Data 2016 VLDB 6.2569019e-05
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