Distal Dynamic Spatial Approximation Forest

Querying large datasets by proximity, using a distance under the metric space model, has a large number of applications in multimedia, pattern recognition, statistics, etc. There is an ever growing number of indexes and algorithms for proximity querying, however there is only a handful of indexes ab...

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Detalles Bibliográficos
Autores principales:	Chávez, Edgar, Di Genaro, María, Reyes, Nora Susana, Roggero, Patricia
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	2016
Materias:	Ciencias Informáticas similarity search dynamism metric spaces non-conventional databases
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/56766
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-56766
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 similarity search dynamism metric spaces non-conventional databases
spellingShingle	Ciencias Informáticas similarity search dynamism metric spaces non-conventional databases Chávez, Edgar Di Genaro, María Reyes, Nora Susana Roggero, Patricia Distal Dynamic Spatial Approximation Forest
topic_facet	Ciencias Informáticas similarity search dynamism metric spaces non-conventional databases
description	Querying large datasets by proximity, using a distance under the metric space model, has a large number of applications in multimedia, pattern recognition, statistics, etc. There is an ever growing number of indexes and algorithms for proximity querying, however there is only a handful of indexes able to perform well without user intervention to select parameters. One of such indexes is the Distal Spatial Approximation Tree (DiSAT) which is parameter-less and has demonstrated to be very efficient outperforming other approaches. The main drawback of the DiSAT is its static nature, that is, once built, it is difficult to add or to remove new elements. This drawback prevents the use of the DiSAT for many interesting applications. In this paper we overcome this weakness. We use a standard technique, the Bentley and Saxe algorithm, to produce a new index which is dynamic while retaining the simplicity and appeal for practitioners of the DiSAT. In order to improve the DiSAF performance, we do not attempt to directly apply the Bentley and Saxe technique, but we enhance its application by taking advantage of our deep knowledge of the DiSAT behavior.
format	Objeto de conferencia Objeto de conferencia
author	Chávez, Edgar Di Genaro, María Reyes, Nora Susana Roggero, Patricia
author_facet	Chávez, Edgar Di Genaro, María Reyes, Nora Susana Roggero, Patricia
author_sort	Chávez, Edgar
title	Distal Dynamic Spatial Approximation Forest
title_short	Distal Dynamic Spatial Approximation Forest
title_full	Distal Dynamic Spatial Approximation Forest
title_fullStr	Distal Dynamic Spatial Approximation Forest
title_full_unstemmed	Distal Dynamic Spatial Approximation Forest
title_sort	distal dynamic spatial approximation forest
publishDate	2016
url	http://sedici.unlp.edu.ar/handle/10915/56766
work_keys_str_mv	AT chavezedgar distaldynamicspatialapproximationforest AT digenaromaria distaldynamicspatialapproximationforest AT reyesnorasusana distaldynamicspatialapproximationforest AT roggeropatricia distaldynamicspatialapproximationforest
bdutipo_str	Repositorios
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Distal Dynamic Spatial Approximation Forest

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