Locality-sensitive hashing
In computer science, locality-sensitive hashing (LSH) is an algorithmic technique that hashes similar input items into the same "buckets" with high probability. (The number of buckets are much smaller than the universe of possible input items.) Since similar items end up in the same buckets, this technique can be used for data clustering and nearest neighbor search. It differs from conventional hashing techniques in that hash collisions are maximized, not minimized. Alternatively, the technique can be seen as a way to reduce the dimensionality of high-dimensional data; high-dimensional input items can be reduced to low-dimensional versions while preserving relative distances between items.
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(1+ε)-approximate nearest neighbor searchAndrei BroderAndrew TridgellApproximate string matchingBag-of-words model in computer visionBioinformatics discovery of non-coding RNAsBloom filterCollaborative filteringContent similarity detectionCount–min sketchDifferentiable neural computerDimensionality reductionDuplicate codeELKIFarthest-first traversalFeature hashingGensimGeocodeHadamard transformHash busterHash collisionHash filterHierarchical clusteringHilbert curveJaccard indexJubatusK-nearest neighbors algorithmLSHLatent semantic analysisLevenshtein distanceList of algorithmsLocality-Sensitive HashingLocality-preserving hashingLocality-sensitive hashingLocality Sensitive HashingLocality preserving hashingLocality sensitive hashingMichael MitzenmacherMinHashMlpack
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Locality-sensitive hashing
In computer science, locality-sensitive hashing (LSH) is an algorithmic technique that hashes similar input items into the same "buckets" with high probability. (The number of buckets are much smaller than the universe of possible input items.) Since similar items end up in the same buckets, this technique can be used for data clustering and nearest neighbor search. It differs from conventional hashing techniques in that hash collisions are maximized, not minimized. Alternatively, the technique can be seen as a way to reduce the dimensionality of high-dimensional data; high-dimensional input items can be reduced to low-dimensional versions while preserving relative distances between items.
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Il locality-sensitive hashing ...... toriale di un insieme di dati.
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In computer science, locality- ...... lity-preserving hashing (LPH).
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Locality sensitive hashing (LS ...... rmatique…[citation nécessaire]
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Locality-sensitive hashing (LS ...... га и косинусного коэффициента.
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局所性鋭敏型ハッシュ(きょくしょせいえいびんがたハッシュ、英 ...... トの数は入力されるデータサンプルの数よりもずっと小さくなる。
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Il locality-sensitive hashing ...... toriale di un insieme di dati.
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In computer science, locality- ...... ative distances between items.
@en
Locality sensitive hashing (LS ...... rmatique…[citation nécessaire]
@fr
Locality-sensitive hashing (LS ...... , «похожих» на искомый шаблон.
@ru
局所性鋭敏型ハッシュ(きょくしょせいえいびんがたハッシュ、英 ...... トの数は入力されるデータサンプルの数よりもずっと小さくなる。
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Locality sensitive hashing
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Locality-sensitive hashing
@en
Locality-sensitive hashing
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Locality-sensitive hashing
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局所性鋭敏型ハッシュ
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