snandasena / optimal-lsh Goto Github PK

This package provides code to implement locality-sensitive hashing (LSH) 
in an optimum fashion.

There are two pieces.  A Python library that implements LSH and a Matlab
routine that calculates the optimum parameters for LSH.

The LSH implementation is based on a tutorial published by IEEE
	Malcolm Slaney, Michael Casey, "Locality-Sensitive Hashing 
	for Finding Nearest Neighbors [Lecture Notes]," 
	Signal Processing Magazine, IEEE , vol.25, no.2, 
	pp.128-131, March 2008
	doi: 10.1109/MSP.2007.914237
	URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4472264&isnumber=4472102
and also available at this URL
	http://www.slaney.org/malcolm/yahoo/Slaney2008-LSHTutorial.pdf

The optimization algorithm is based on this article, which is currently
under review.  Send email to [email protected] for a preprint
	Malcolm Slaney, Yury Lifshits, Junfeng He, "Optimal
	Locality-Sensitive Hashing," Submitted to Proceedings of the 
	IEEE, Special Issue on Web-Scale Multimedia, Summer 2012.

Send bug reports and/or comments to 
	[email protected]

################################################################
Copyright (c) 2011, Yahoo! Inc.
All rights reserved.

Redistribution and use of this software in source and binary forms, 
with or without modification, are permitted provided that the following 
conditions are met:

* Redistributions of source code must retain the above
  copyright notice, this list of conditions and the
  following disclaimer.

* Redistributions in binary form must reproduce the above
  copyright notice, this list of conditions and the
  following disclaimer in the documentation and/or other
  materials provided with the distribution.

* Neither the name of Yahoo! Inc. nor the names of its
  contributors may be used to endorse or promote products
  derived from this software without specific prior
  written permission of Yahoo! Inc.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS 
IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED 
TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A 
PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT 
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, 
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT 
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, 
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY 
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE 
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.