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

@article{citeulike:3866140, abstract = {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.}, author = {Slaney, M. and Casey, M.}, booktitle = {Signal Processing Magazine, IEEE}, citeulike-article-id = {3866140}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/MSP.2007.914237}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4472264}, doi = {10.1109/MSP.2007.914237}, journal = {Signal Processing Magazine, IEEE}, keywords = {geography, hash, neighbours, search}, number = {2}, pages = {128--131}, posted-at = {2009-01-09 00:29:41}, priority = {3}, title = {Locality-Sensitive Hashing for Finding Nearest Neighbors [Lecture Notes]}, url = {http://dx.doi.org/10.1109/MSP.2007.914237}, volume = {25}, year = {2008} }

TY - JOUR ID - citeulike:3866140 L3 - citeulike-article-id:3866140 N2 - 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. IS - 2 JF - Signal Processing Magazine, IEEE EP - 131 TI - Locality-Sensitive Hashing for Finding Nearest Neighbors [Lecture Notes] VL - 25 T2 - Signal Processing Magazine, IEEE SP - 128 KW - geography KW - hash KW - neighbours KW - search AU - Slaney, M AU - Casey, M PY - 2008/// UR - http://dx.doi.org/10.1109/MSP.2007.914237 ER -