On Locality-sensitive Indexing in Generic Metric Spaces

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F10%3A00044857" target="_blank" >RIV/00216224:14330/10:00044857 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
On Locality-sensitive Indexing in Generic Metric Spaces
Original language description
The concept of Locality-sensitive Hashing (LSH) has been successfully used for searching in high-dimensional data and a number of locality-preserving hash functions have been introduced. In order to extend the applicability of the LSH approach to a general metric space, we focus on a recently presented Metric Index (M-Index), we redefine its hashing and searching process in the terms of LSH, and perform extensive measurements on two datasets to verify that the M-Index fulfills the conditions of the LSHconcept. We widely discuss "optimal" properties of LSH functions and the efficiency of a given LSH function with respect to kNN queries. The results also indicate that the M-Index hashing and searching is more efficient than the tested standard LSH approach for Euclidean distance.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
3rd International Conference on Similarity Search and Applications
ISBN
978-1-4503-0420-7
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
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Publisher name
ACM Press
Place of publication
New York
Event location
Istanbul, Turkey
Event date
Sep 18, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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