Talk:Locality-sensitive hashing

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Suggestion to remove Nilsimsa Hash section

The Nilsimsa Hash does not really fit into the LSH definition(s) (Indyk's or Charikar's). Consequently, there is no way to plug into the common framework of LSH and obtain good index-size and query performance guarantees --- one of the strengths of LSH approaches. Hence, I suggest this section should be removed, or at least not in the current place (in the same level with random projection, simhash, and p-stable based lsh).

Untitled

Just made the page. There are some variations among definitions of LSH - I am using Charikar's. Flamholz 19:40, 6 June 2007 (UTC)[reply]

Charikar's definition is too narrow, though a bit easy to understand by beginners.

Definition of an LSH

I don't think the current definition really makes sense, although maybe it could be modified a little to work.

Specifically: for a metric phi(x,y), we have phi(x,y)->0 (intuitively) as x->y. But if Pr[h(x)=h(y)] -> 0 as x->y, that's bad! I mean, that is just about the opposite of a locality-sensitive hash.

One fix might be to say Pr[h(a) = h(b)] = 1 - phi(a,b) instead.

Although it would also be nice to allow for general boolean combinations of hashes, such as simultaneously hashing to many different values, and calling it a hit if some combination thereof actually collide. —Preceding unsigned comment added by PhiloMath (talk • contribs) 07:14, 5 December 2007 (UTC)[reply]

I totally agree. The definition as it stands is wrong. The phi(a,b) is a similarity not a distance or metric (mathematics). Another error is that the Jaccard_index which is a similarity but is currently is referred to as the "Jaccard distance". Notice that the correct definition looks like a probabilistic version of Injective_mapping. cmobarry (talk) 17:26, 20 December 2007 (UTC)[reply]

Added another variant of LSH definition

We added the Indyk-Motwani definition of the LSH family, plus an LSH family for the Hamming space (by bit sampling), as well as the LSH algorithm for the nearest neighbor search (approximate). Alex and Piotr. 128.30.48.53 (talk) 02:13, 7 February 2008 (UTC)[reply]

Hey guys, i have a question.

in the last section:

LSH Algorithm for the Nearest Neighbor Search

... it is being claimed that : ....

query time: $O(L(kt+dnP_{2}^{k}))$ ;

i am trying to figure out from where does the $P_{2}$ comes from... why is the probability for colision is $P_{2}$ ?

can someone please shed some light on this? —Preceding unsigned comment added by Caligola0 (talk • contribs) 18:01, 18 June 2009 (UTC)[reply]

Relation to Vector Quantization?

hi - could someone clarify the relation to Vector Quantization please? --mcld (talk) 09:21, 8 April 2010 (UTC)[reply]