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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
11228
Venue
VLDB
Year
2016
Pagerank
6.5919471e-05
Overall Rank
3,951 | 72.55%
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
125 Approximate String Joins in a Database (Almost) for Free 2001 VLDB 0.00044946098
394 Big Data Integration 2013 VLDB 0.0002447017
1,146 Web-scale Data Integration: You can only afford to Pay As You Go 2007 CIDR 0.0001367088
4,967 Supervised Meta-blocking 2014 VLDB 5.7939544e-05
5,219 Schema-agnostic vs Schema-based Configurations for Blocking Methods on Homogeneous Data 2016 VLDB 5.6196254e-05
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