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Everything about MinHash

Data mining technique

In computer science and data mining, MinHash is a technique for quickly estimating how similar two sets are. The scheme was published by Andrei Broder in a 1997 conference, and initially used in the AltaVista search engine to detect duplicate web pages and eliminate them from search results. It has also been applied in large-scale clustering problems, such as clustering documents by the similarity of their sets of words. Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: MinHashA 5-minute orientation
  2. Skim a recent paper: RabbitTClust: enabling fast clustering analysis of millions of bacteria genomes with MinHash sketchesInfluential work since 2022
  3. Read the landmark paper: Mash: fast genome and metagenome distance estimation using MinHashCited 3,418 times
  4. Go sideways: Locality-sensitive hashingA closely related topic
  5. Go sideways: Count–min sketchA closely related topic

đź“– Definitions

No dictionary entry for this exact phrase.

🗂️ The subject at a glance

  1. Jaccard similarity and minimum hash values
  2. Algorithm
  3. Incorporating weights
  4. Min-wise independent permutations
  5. Applications
  6. Other uses
  7. Evaluation and benchmarks

🏆 Landmark papers (most cited)

🆕 Influential since 2022

đź“š Books worth reading

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đź”— Related topics