Introduction to Locality-Sensitive Hashing
Locality-sensitive hashing (LSH) is a set of techniques that dramatically speed up search-for-neighbors or near-duplication detection on data. These techniques can be used, for example, to filter out duplicates of scraped web pages at an impressive speed, or to perform near-constant-time lookups of nearby points from a geospatial data set.
Introduction to Locality-Sensitive Hashing \(\newcommand{\latexonlyrule}[2]{}\) Introduction to Locality-Sensitive Hashing Tyler Neylon — (Got a machine learning project? Email me: tyler@unboxresearch.com ) 521.2018 [Formats: html | pdf | kindle pdf ] Locality-sensitive hashing (LSH) is a set of techniques that dramatically speed up search-for-neighbors or near-duplication detection on data. These techniques can be used, for example, to filter out duplicates of scraped web pages at an impressive speed, or to perform near-constant-time lookups of nearby points from a geospatial data set. Figure
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