局部敏感散列
地点
散列函数
计算机科学
k-最近邻算法
数据挖掘
理论计算机科学
算法
哈希表
情报检索
人工智能
计算机安全
语言学
哲学
作者
Omid Jafari,Preeti Maurya,Parth Nagarkar,Khandker Mushfiqul Islam,Chidambaram Crushev
出处
期刊:Cornell University - arXiv
日期:2021-02-17
被引量:2
摘要
Finding nearest neighbors in high-dimensional spaces is a fundamental operation in many diverse application domains. Locality Sensitive Hashing (LSH) is one of the most popular techniques for finding approximate nearest neighbor searches in high-dimensional spaces. The main benefits of LSH are its sub-linear query performance and theoretical guarantees on the query accuracy. In this survey paper, we provide a review of state-of-the-art LSH and Distributed LSH techniques. Most importantly, unlike any other prior survey, we present how Locality Sensitive Hashing is utilized in different application domains.
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