D-cache: Universal Distance Cache for Metric Access Methods

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F12%3A10045850" target="_blank" >RIV/00216208:11320/12:10045850 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.computer.org/portal/web/csdl/doi/10.1109/TKDE.2011.19" target="_blank" >http://www.computer.org/portal/web/csdl/doi/10.1109/TKDE.2011.19</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TKDE.2011.19" target="_blank" >10.1109/TKDE.2011.19</a>

Jazyk výsledku

angličtina

Název v původním jazyce

D-cache: Universal Distance Cache for Metric Access Methods

Popis výsledku v původním jazyce

An important research issue in multimedia databases is the retrieval of similar objects. For most applications in multimedia databases, an exact search is not meaningful. Thus, much effort has been devoted to develop efficient and effective similarity search techniques. A recent approach, that has been shown to improve the effectiveness of similarity search in multimedia databases, resorts to the usage of combinations of metrics where the desirable contribution (weight) of each metric is chosen at querytime. This paper presents a framework for adapting Metric Indexes to Multi-Metric indexes, that is to support similarity queries with dynamic combinations of metric functions. The adapted indexes are built with a single distance function and store partial distances to estimate the weighed distances. An experimental evaluation shows that the adapted indexes may be as efficient as the original metric indexes.

Název v anglickém jazyce

D-cache: Universal Distance Cache for Metric Access Methods

Popis výsledku anglicky

An important research issue in multimedia databases is the retrieval of similar objects. For most applications in multimedia databases, an exact search is not meaningful. Thus, much effort has been devoted to develop efficient and effective similarity search techniques. A recent approach, that has been shown to improve the effectiveness of similarity search in multimedia databases, resorts to the usage of combinations of metrics where the desirable contribution (weight) of each metric is chosen at querytime. This paper presents a framework for adapting Metric Indexes to Multi-Metric indexes, that is to support similarity queries with dynamic combinations of metric functions. The adapted indexes are built with a single distance function and store partial distances to estimate the weighed distances. An experimental evaluation shows that the adapted indexes may be as efficient as the original metric indexes.

Druh

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

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GA201%2F09%2F0683" target="_blank" >GA201/09/0683: Vyhledávání v rozsáhlých multimediálních databázích</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název periodika

IEEE Transactions on Knowledge and Data Engineering

ISSN

1041-4347

e-ISSN

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Svazek periodika

24

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

14

Strana od-do

868-881

Kód UT WoS článku

000301746800008

EID výsledku v databázi Scopus

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