Approximate Joins: Concepts and Techniques

Summary: Tutorial survey of approximate joins, framing variants as optimization problems and comparing approximate-match predicates. Unifies tuple-similarity decisions with cross-dataset join techniques, while highlighting open research challenges. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 9482
Venue: VLDB
Year: 2005
Pagerank: 5.2528121e-05
Overall Rank: 9,584 | 34.25%
DOI: -

Incoming Non-self Citations Over Time

Authors

1. Nick Koudas (University of Toronto)
2. Divesh Srivastava (AT&T)

BibTeX Citation

@article{koudas_vldb05,
        title = {{Approximate Joins: Concepts and Techniques}},
        author = {Koudas, Nick and Srivastava, Divesh},
        journal = {PVLDB},
        series = {{VLDB} '05},
        volume = {31},
        pages = {1363--1366},
        year = {2005}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
254	Record Linkage: Similarity Measures and Algorithms	2006	SIGMOD	0.00023199211
12,671	Randomized Algorithms for Data Reconciliation in Wide Area Aggregate Query Processing	2007	VLDB	5.093636e-05
13,812	Using SPIDER: An Experience Report	2006	SIGMOD	-

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
1,484	Data Quality and Data Cleaning: An Overview	2003	SIGMOD	0.00010631363

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