Dynamic Spatial Approximation Trees with clusters for secondary memory

Metric space searching is an emerging technique to address the problem of e cient similarity searching in many applications, including multimedia databases and other repositories handling complex objects. Although promising, the metric space approach is still immature in several aspects that are wel...

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Detalles Bibliográficos
Autores principales: Britos, Luís, Printista, Alicia Marcela, Reyes, Nora Susana
Formato: Objeto de conferencia
Lenguaje:Español
Publicado: 2010
Materias:
Ciencias Informáticas
secondary memory
Base de Datos
Data mining
Metrics
clusters
data bases
DSACL tree
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/19337
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-19337
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Español
topic Ciencias Informáticas
secondary memory
Base de Datos
Data mining
Metrics
clusters
data bases
DSACL tree
spellingShingle Ciencias Informáticas
secondary memory
Base de Datos
Data mining
Metrics
clusters
data bases
DSACL tree
Britos, Luís
Printista, Alicia Marcela
Reyes, Nora Susana
Dynamic Spatial Approximation Trees with clusters for secondary memory
topic_facet Ciencias Informáticas
secondary memory
Base de Datos
Data mining
Metrics
clusters
data bases
DSACL tree
description Metric space searching is an emerging technique to address the problem of e cient similarity searching in many applications, including multimedia databases and other repositories handling complex objects. Although promising, the metric space approach is still immature in several aspects that are well established in traditional databases. In particular, most indexing schemes are not dynamic. From the few dynamic indexes, even fewer work well in secondary memory. That is, most of them need the index in main memory in order to operate e ciently. In this paper we introduce a secondary-memory variant of the Dynamic Spatial Approximation Tree with Clusters (DSACL-tree) which has shown to be competitive in main memory. The resulting index handles well the secondary memory scenario and is competitive with the state of the art. The resulting index is a much more practical data structure that can be useful in a wide range of database applications.
format Objeto de conferencia
Objeto de conferencia
author Britos, Luís
Printista, Alicia Marcela
Reyes, Nora Susana
author_facet Britos, Luís
Printista, Alicia Marcela
Reyes, Nora Susana
author_sort Britos, Luís
title Dynamic Spatial Approximation Trees with clusters for secondary memory
title_short Dynamic Spatial Approximation Trees with clusters for secondary memory
title_full Dynamic Spatial Approximation Trees with clusters for secondary memory
title_fullStr Dynamic Spatial Approximation Trees with clusters for secondary memory
title_full_unstemmed Dynamic Spatial Approximation Trees with clusters for secondary memory
title_sort dynamic spatial approximation trees with clusters for secondary memory
publishDate 2010
url http://sedici.unlp.edu.ar/handle/10915/19337
work_keys_str_mv AT britosluis dynamicspatialapproximationtreeswithclustersforsecondarymemory
AT printistaaliciamarcela dynamicspatialapproximationtreeswithclustersforsecondarymemory
AT reyesnorasusana dynamicspatialapproximationtreeswithclustersforsecondarymemory
bdutipo_str Repositorios
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