Optimizing the spatial approximation tree from the root

Many computational applications need to look for information in a database. Nowadays, the predominance of nonconventional databases makes the similarity search (i.e., searching elements of the database that are "similar" to a given query) becomes a preponderant concept. The Spatial Approxi...

Descripción completa

Detalles Bibliográficos
Autores principales: Gómez, Alejandro J., Ludueña, Verónica, Reyes, Nora Susana
Formato: Articulo
Lenguaje:Inglés
Publicado: 2008
Materias:
Ciencias Informáticas
Base de Datos
Metrics
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/9632
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Jul08-9.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-9632
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Base de Datos
Metrics
spellingShingle Ciencias Informáticas
Base de Datos
Metrics
Gómez, Alejandro J.
Ludueña, Verónica
Reyes, Nora Susana
Optimizing the spatial approximation tree from the root
topic_facet Ciencias Informáticas
Base de Datos
Metrics
description Many computational applications need to look for information in a database. Nowadays, the predominance of nonconventional databases makes the similarity search (i.e., searching elements of the database that are "similar" to a given query) becomes a preponderant concept. The Spatial Approximation Tree has been shown that it compares favorably against alternative data structures for similarity searching in metric spaces of medium to high dimensionality ("difficult" spaces) or queries with low selectivity. However, for the construction process the tree root has been randomly selected and the tree ,in its shape and performance, is completely determined by this selection. Therefore, we are interested in improve mainly the searches in this data structure trying to select the tree root so to reflect some of the own characteristics of the metric space to be indexed. We regard that selecting the root in this way it allows a better adaption of the data structure to the intrinsic dimensionality of the metric space considered, so also it achieves more efficient similarity searches.
format Articulo
Articulo
author Gómez, Alejandro J.
Ludueña, Verónica
Reyes, Nora Susana
author_facet Gómez, Alejandro J.
Ludueña, Verónica
Reyes, Nora Susana
author_sort Gómez, Alejandro J.
title Optimizing the spatial approximation tree from the root
title_short Optimizing the spatial approximation tree from the root
title_full Optimizing the spatial approximation tree from the root
title_fullStr Optimizing the spatial approximation tree from the root
title_full_unstemmed Optimizing the spatial approximation tree from the root
title_sort optimizing the spatial approximation tree from the root
publishDate 2008
url http://sedici.unlp.edu.ar/handle/10915/9632
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Jul08-9.pdf
work_keys_str_mv AT gomezalejandroj optimizingthespatialapproximationtreefromtheroot
AT luduenaveronica optimizingthespatialapproximationtreefromtheroot
AT reyesnorasusana optimizingthespatialapproximationtreefromtheroot
bdutipo_str Repositorios
_version_ 1764820492020088834

Ejemplares similares