Large-scale similarity data management with distributed Metric Index

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F12%3A00057505" target="_blank" >RIV/00216224:14330/12:00057505 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.ipm.2010.12.004" target="_blank" >http://dx.doi.org/10.1016/j.ipm.2010.12.004</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ipm.2010.12.004" target="_blank" >10.1016/j.ipm.2010.12.004</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Large-scale similarity data management with distributed Metric Index

Popis výsledku v původním jazyce

Metric space is a universal and versatile model of similarity that can be applied in various areas of non-text information retrieval. However, a general, efficient and scalable solution for metric data management is still a resisting research challenge.In this work, we try to make an important step towards such management system that would be able to scale to data collections of billions of objects. We propose a distributed index structure for similarity data management called the Metric Index (M-Index) which can answer queries in precise and approximate manner. This technique can take advantage of any distributed hash table that supports interval queries and utilize it as an underlying index. We have performed numerous experiments to test various settings of the M-Index structure and we have proved its usability by developing a full-featured publicly-available Web application.

Název v anglickém jazyce

Large-scale similarity data management with distributed Metric Index

Popis výsledku anglicky

Metric space is a universal and versatile model of similarity that can be applied in various areas of non-text information retrieval. However, a general, efficient and scalable solution for metric data management is still a resisting research challenge.In this work, we try to make an important step towards such management system that would be able to scale to data collections of billions of objects. We propose a distributed index structure for similarity data management called the Metric Index (M-Index) which can answer queries in precise and approximate manner. This technique can take advantage of any distributed hash table that supports interval queries and utilize it as an underlying index. We have performed numerous experiments to test various settings of the M-Index structure and we have proved its usability by developing a full-featured publicly-available Web application.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název periodika

Information Processing and Management

ISSN

0306-4573

e-ISSN

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Svazek periodika

48

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

18

Strana od-do

855-872

Kód UT WoS článku

000307682100005

EID výsledku v databázi Scopus

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