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Selectivity Estimation for Fuzzy String Predicates in Large Data Sets

Summary: Proposes Sepia, a histogram-based selectivity estimator for fuzzy string predicates. It clusters strings, builds per-cluster and global histograms, and uses a pivot to propagate q–s similarity via edit distance; extensible to other similarity measures and robust to nonuniform errors. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9321
Venue
VLDB
Year
2005
Pagerank
6.1898903e-05
Overall Rank
4,438 | 69.13%
DOI
-

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