
@Reference(authors="M. Datar and N. Immorlica and P. Indyk and V. S. Mirrokni", title="Locality-sensitive hashing scheme based on p-stable distributions", booktitle="Proc. 20th annual symposium on Computational geometry", url="http://dx.doi.org/10.1145/997817.997857") public class ManhattanHashFunctionFamily extends AbstractHashFunctionFamily
Locality-sensitive hashing scheme based on p-stable distributions
M. Datar and N. Immorlica and P. Indyk and V. S. Mirrokni
Proc. 20th annual symposium on Computational geometry
| Modifier and Type | Class and Description |
|---|---|
static class |
ManhattanHashFunctionFamily.Parameterizer
Parameterization class.
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k, proj, random, width| Constructor and Description |
|---|
ManhattanHashFunctionFamily(RandomFactory random,
double width,
int k)
Constructor.
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| Modifier and Type | Method and Description |
|---|---|
boolean |
isCompatible(DistanceFunction<?,?> df)
Check whether the given distance function can be accelerated using this
hash family.
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generateHashFunctions, getInputTypeRestrictionpublic ManhattanHashFunctionFamily(RandomFactory random, double width, int k)
random - Random generatorwidth - Bin widthk - Number of projections to combine.public boolean isCompatible(DistanceFunction<?,?> df)
LocalitySensitiveHashFunctionFamilydf - Distance function.true when appropriate.