BM-index: Balanced Metric Space Index based on Weighted Voronoi Partitioning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F19%3A00109747" target="_blank" >RIV/00216224:14330/19:00109747 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-030-28730-6_21" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-28730-6_21</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-28730-6_21" target="_blank" >10.1007/978-3-030-28730-6_21</a>

Jazyk výsledku

angličtina

Název v původním jazyce

BM-index: Balanced Metric Space Index based on Weighted Voronoi Partitioning

Popis výsledku v původním jazyce

Processing large volumes of various data needs index structures that can efficiently organize them on secondary memory. Methods based on so-called pivot permutations have become popular in addressing these requirements because of their tremendous querying performance. They localize data objects by ordering preselected anchor objects by their distances to the data objects, and so no coordinate system is exploited to partition the data. This represents a generic solution for unstructured and high-dimensional data. In principle, pivot permutations implement recursive Voronoi tessellation. Also, due to the fixed preselected anchors, such partitioning cannot adapt to the data distribution and leads to very unbalanced cells. In this paper, we address this issue and propose a novel schema called BM-index. It exploits weighted Voronoi partitioning to create pivot permutations that adapt to data distribution. Secondary memory is then accessed efficiently with respect to the existing disk-oriented structures, such as M-index. We present an algorithm to balance the data partitions, and we show its correctness. In experiments on a real-life image collection CoPhIR, we show superior performance in I/O costs when evaluating k-nearest neighbors queries.

Název v anglickém jazyce

BM-index: Balanced Metric Space Index based on Weighted Voronoi Partitioning

Popis výsledku anglicky

Processing large volumes of various data needs index structures that can efficiently organize them on secondary memory. Methods based on so-called pivot permutations have become popular in addressing these requirements because of their tremendous querying performance. They localize data objects by ordering preselected anchor objects by their distances to the data objects, and so no coordinate system is exploited to partition the data. This represents a generic solution for unstructured and high-dimensional data. In principle, pivot permutations implement recursive Voronoi tessellation. Also, due to the fixed preselected anchors, such partitioning cannot adapt to the data distribution and leads to very unbalanced cells. In this paper, we address this issue and propose a novel schema called BM-index. It exploits weighted Voronoi partitioning to create pivot permutations that adapt to data distribution. Secondary memory is then accessed efficiently with respect to the existing disk-oriented structures, such as M-index. We present an algorithm to balance the data partitions, and we show its correctness. In experiments on a real-life image collection CoPhIR, we show superior performance in I/O costs when evaluating k-nearest neighbors queries.

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/EF16_019%2F0000822" target="_blank" >EF16_019/0000822: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur</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

2019

Kód důvěrnosti údajů

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

Název statě ve sborníku

Advances in Databases and Information Systems, 23th East European Conference, ADBIS 2019

ISBN

9783030287290

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

17

Strana od-do

337-353

Název nakladatele

Springer International Publishing

Místo vydání

Cham

Místo konání akce

Slovenia

Datum konání akce

1. 1. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000558104700024