A binomial approximation to the sample overlap likelihood yields a simple estimator for Jaccard containment, but several of the paper's error bounds and sample size formulas are not rigorously supported.
SuperMinHash - A New Minwise Hashing Algorithm for Jaccard Similarity Estimation
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This paper presents a new algorithm for calculating hash signatures of sets which can be directly used for Jaccard similarity estimation. The new approach is an improvement over the MinHash algorithm, because it has a better runtime behavior and the resulting signatures allow a more precise estimation of the Jaccard index.
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Sampling-Based Estimation of Jaccard Containment and Similarity
A binomial approximation to the sample overlap likelihood yields a simple estimator for Jaccard containment, but several of the paper's error bounds and sample size formulas are not rigorously supported.