Locality-Sensitive Hashing for Finding Nearest Neighbors

1053-5888/08/$20.00©2008IEEE IEEE SIGNAL PROCESSING MAGAZINE [128] MARCH 2008 T he Internet has brought us a wealth of data, all now available at our fingertips. We can easily carry in our pockets thousands of songs, hundreds of thousands of images, and hundreds of hours of video. But even with the rapid growth of computer performance, we don’t have the processing power to search this amount of data by brute force. 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.