# BagMinHash - Minwise Hashing Algorithm for Weighted Sets

arXiv: https://arxiv.org/abs/1802.03914 · HTML: https://mlsanity.com/paper/1802.03914/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Feb 2018.

## Built on by (most cited first, 3 of 3)

- [Differentially Private One Permutation Hashing and Bin-wise Consistent Weighted Sampling](https://mlsanity.com/paper/2306.07674/) (2023)
- [Fast Gumbel-Max Sketch and its Applications](https://mlsanity.com/paper/2302.05176/) (2023)
- [Pb-Hash: Partitioned b-bit Hashing](https://mlsanity.com/paper/2306.15944/) (2023)

## Abstract (arXiv)

Minwise hashing has become a standard tool to calculate signatures which allow direct estimation of Jaccard similarities. While very efficient algorithms already exist for the unweighted case, the calculation of signatures for weighted sets is still a time consuming task. BagMinHash is a new algorithm that can be orders of magnitude faster than current state of the art without any particular restrictions or assumptions on weights or data dimensionality. Applied to the special case of unweighted sets, it represents the first efficient algorithm producing independent signature components. A series of tests finally verifies the new algorithm and also reveals limitations of other approaches published in the recent past.