MinHash.jl

Fast and generic implementation of the minhash algorithm
Author jakobnissen
Popularity
14 Stars
Updated Last
11 Months Ago
Started In
March 2020

MinHash

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Efficient minhashing in Julia

MinHash.jl offers generic, efficient MinHash sketching, and functions to efficiently compute the number of shared minhashes between sketches. This package is envisioned to be used as a dependency for other Julia packages that needs minhashing.

Interface

Types

MinHasher{F}(s::Integer)

A MinHasher object performs the minhashing, using function F as a hash function, and storing the s smallest hashes only. F defaults to Base.hash.

MinHashSketch(::MinHasher)

Stores the information of a MinHasher (namely, the hash function, maximal number of hashes, and the hashes themselves) in a more efficient type. This type should be used to store the actual hashes.

Methods

update!(::MinHasher, it)

Iterate over it, adding each element to the minhasher.

sketch(F, it, s::Integer) Hash all elements of it using function F, storing at most the s smallest hashes. Equivalent to:

hasher = MinHasher{F}(s)
update!(hasher, it)
return MinHashSketch(hasher)

sketch(it, s::Integer)

Same as sketch(Base.hash, it, s)

intersectionlength(a::MinHashSketch, b::MinHashSketch)

Efficiently compute the number of hashes both in a and b. Does not check that the hash functions for the two sketches are the same, result will be meaningless if they are not.

intersectionlength(::AbstractVector{MinHashSketch})

Efficiently compute a lower triangular matrix (of type Matrix{Int}) of shared hashes for all pairs in the input vector. For long vectors, this is much more efficient than calculating the distances pairwise.