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LSH
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Overview
Developed byPiotr Indyk and Rajeev Motwani
Founded1998
Use casesimilarity search in high-dimensional spaces
Knowledge graph stats
Claims44
Avg confidence90%
Avg freshness100%
Last updatedUpdated 5 days ago
WikidataQ1757710
Trust distribution
100% unverified
Governance
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LSH

concept

Locality-Sensitive Hashing technique for approximate nearest neighbor search by hashing similar items together.

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primary use case

ValueTrustConfidenceFreshnessSources
similarity search in high-dimensional spaces○UnverifiedHighFresh1
approximate nearest neighbor search○UnverifiedHighFresh1
approximate nearest neighbor search in high-dimensional spaces○UnverifiedHighFresh1
high-dimensional similarity search○UnverifiedHighFresh1
dimensionality reduction for similarity search○UnverifiedHighFresh1
dimensionality reduction for high-dimensional data○UnverifiedHighFresh1
dimensionality reduction○UnverifiedModerateFresh1
similarity search in machine learning applications○UnverifiedModerateFresh1
web search and information retrieval○UnverifiedModerateFresh1
duplicate detection○UnverifiedModerateFresh1

based on

ValueTrustConfidenceFreshnessSources
hash functions○UnverifiedHighFresh1
hash functions with locality preservation property○UnverifiedHighFresh1
hash functions that preserve locality○UnverifiedHighFresh1

supports model

ValueTrustConfidenceFreshnessSources
MinHash for Jaccard similarity○UnverifiedHighFresh1
random projection for cosine similarity○UnverifiedModerateFresh1
MinHash for set similarity○UnverifiedModerateFresh1
random projection for Euclidean distance○UnverifiedModerateFresh1

developed by

ValueTrustConfidenceFreshnessSources
Piotr Indyk and Rajeev Motwani○UnverifiedHighFresh1
Piotr Indyk○UnverifiedModerateFresh1
Rajeev Motwani○UnverifiedModerateFresh1

alternative to

ValueTrustConfidenceFreshnessSources
brute force search○UnverifiedHighFresh1
exhaustive nearest neighbor search○UnverifiedHighFresh1
brute force nearest neighbor search○UnverifiedHighFresh1
exhaustive search○UnverifiedHighFresh1
k-d trees for high-dimensional spaces○UnverifiedHighFresh1
k-d trees for high-dimensional nearest neighbor search○UnverifiedModerateFresh1
k-d trees○UnverifiedModerateFresh1
k-d trees for high-dimensional data○UnverifiedModerateFresh1

founded year

ValueTrustConfidenceFreshnessSources
1998○UnverifiedHighFresh1

supports protocol

ValueTrustConfidenceFreshnessSources
Jaccard similarity○UnverifiedModerateFresh1
cosine similarity○UnverifiedModerateFresh1
Hamming distance○UnverifiedModerateFresh1

integrates with

ValueTrustConfidenceFreshnessSources
machine learning libraries○UnverifiedModerateFresh1
machine learning frameworks for similarity search○UnverifiedModerateFresh1
Apache Spark MLlib○UnverifiedModerateFresh1

Alternatives & Similar Tools

brute force search
alternative to
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exhaustive nearest neighbor search
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brute force nearest neighbor search
alternative to
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exhaustive search
alternative to
Compare →
k-d trees for high-dimensional spaces
alternative to
Compare →
k-d trees for high-dimensional nearest neighbor search
alternative to
Compare →
k-d trees
alternative to
Compare →
k-d trees for high-dimensional data
alternative to
Compare →

Commonly Used With

machine learning librariesmachine learning frameworks for similarity searchApache Spark MLlib

Related entities

Claim count: 44Last updated: 4/5/2026Edit history