Sketches with Unbalanced Bits for Similarity Search

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F17%3A00095051" target="_blank" >RIV/00216224:14330/17:00095051 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-68474-1_4" target="_blank" >http://dx.doi.org/10.1007/978-3-319-68474-1_4</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-68474-1_4" target="_blank" >10.1007/978-3-319-68474-1_4</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Sketches with Unbalanced Bits for Similarity Search

Popis výsledku v původním jazyce

In order to accelerate efficiency of similarity search, compact bit-strings compared by the Hamming distance, so called sketches, have been proposed as a form of dimensionality reduction. To maximize the data compression and, at the same time, minimize the loss of information, sketches typically have the following two properties: (1) each bit divides datasets approximately in halves, i.e. bits are balanced, and (2) individual bits have low pairwise correlations, preferably zero. It has been shown that sketches with such properties are minimal with respect to the retained information. However, they are very difficult to index due to the dimensionality curse -- the range of distances is rather narrow and the distance to the nearest neighbour is high. We suggest to use sketches with unbalanced bits and we analyse their properties both analytically and experimentally. We show that such sketches can achieve practically the same quality of similarity search and they are much easier to index thanks to the decrease of distances to the nearest neighbours.

Název v anglickém jazyce

Sketches with Unbalanced Bits for Similarity Search

Popis výsledku anglicky

In order to accelerate efficiency of similarity search, compact bit-strings compared by the Hamming distance, so called sketches, have been proposed as a form of dimensionality reduction. To maximize the data compression and, at the same time, minimize the loss of information, sketches typically have the following two properties: (1) each bit divides datasets approximately in halves, i.e. bits are balanced, and (2) individual bits have low pairwise correlations, preferably zero. It has been shown that sketches with such properties are minimal with respect to the retained information. However, they are very difficult to index due to the dimensionality curse -- the range of distances is rather narrow and the distance to the nearest neighbour is high. We suggest to use sketches with unbalanced bits and we analyse their properties both analytically and experimentally. We show that such sketches can achieve practically the same quality of similarity search and they are much easier to index thanks to the decrease of distances to the nearest neighbours.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Centrum pro multi-modální interpretaci dat velkého rozsahu</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Similarity Search and Applications: 10th International Conference, SISAP 2017, Munich, Germany, October 4-6, 2017, Proceedings

ISBN

9783319684741

ISSN

—

e-ISSN

—

Počet stran výsledku

11

Strana od-do

53-63

Název nakladatele

Springer International Publishing

Místo vydání

Cham

Místo konání akce

Mnichov, Německo

Datum konání akce

4. 10. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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