Approximate Joins: Concepts and Techniques

Summary: Tutorial on approximate joins for data with typos; formalizes flavors as optimization problems and surveys similarity metrics. Contrast predicates by algorithmic properties; map pairwise similarity to joins; outline scalable directions for joins. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 9292
Venue: VLDB
Year: 2005
Pagerank: 4.3399748e-05
Overall Rank: 9,436 | 34.42%
DOI: -

Incoming Non-self Citations Over Time

Authors

1. Nick Koudas
2. Divesh Srivastava

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
321	Record Linkage: Similarity Measures and Algorithms	2006	SIGMOD	0.00027524716
12,487	Randomized Algorithms for Data Reconciliation in Wide Area Aggregate Query Processing	2007	VLDB	4.1905499e-05
13,625	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
508	Data Quality and Data Cleaning: An Overview	2003	SIGMOD	0.00021473523

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