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)
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| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,439 | Approximating Predicates and Expressive Queries on Probabilistic Databases | 2008 | PODS | 6.1806955e-05 |
| 4,033 | Flexible String Matching Against Large Databases in Practice | 2004 | VLDB | 6.5125692e-05 |
| 373 | Selectivity Estimation using Probabilistic Models | 2001 | SIGMOD | 0.00025354685 |
| 11,987 | Similarity Joins for Uncertain Strings | 2014 | SIGMOD | 4.1905499e-05 |
| 4,907 | Probabilistic String Similarity Joins | 2010 | SIGMOD | 5.8365853e-05 |
| 63 | Improved Histograms for Selectivity Estimation of Range Predicates | 1996 | SIGMOD | 0.00063595699 |
| 5,066 | A Comparison of Selectivity Estimators for Range Queries on Metric Attributes | 1999 | SIGMOD | 5.7157182e-05 |
| 2,168 | Selectivity Estimation For Boolean Queries | 2000 | PODS | 9.3877451e-05 |
| 896 | Selectivity Estimation and Query Optimization in Large Databases with Highly Skewed Distributions of Column Values | 1988 | VLDB | 0.00015486851 |
| 3,229 | Extending Q-Grams to Estimate Selectivity of String Matching with Low Edit Distance | 2007 | VLDB | 7.3390133e-05 |