By Topic

Locality-Sensitive Hashing for Finding Nearest Neighbors [Lecture Notes]

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)

This lecture note describes a technique known as locality-sensitive hashing (LSH) that allows one to quickly find similar entries in large databases. This approach belongs to a novel and interesting class of algorithms that are known as randomized algorithms. A randomized algorithm does not guarantee an exact answer but instead provides a high probability guarantee that it will return the correct answer or one close to it. By investing additional computational effort, the probability can be pushed as high as desired.

Published in:

Signal Processing Magazine, IEEE  (Volume:25 ,  Issue: 2 )