An Efficient Dynamic Version of the Distal Spatial Approximation Trees

Metric space indices make searches for similar objects more efficient in various applications, including multimedia databases and other repositories which handle complex and unstructured objects. Although there are a plethora of indexes to speed up similarity searches, the Distal Spatial Approximati...

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Detalles Bibliográficos
Autores principales: Chávez, Edgar, Di Genaro, María E., Reyes, Nora Susana
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2022
Materias:
Ciencias Informáticas
similarity search
dynamism
metric spaces
non-conventional databases
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/149651
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-149651
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 E.
Reyes, Nora Susana
An Efficient Dynamic Version of the Distal Spatial Approximation Trees
topic_facet Ciencias Informáticas
similarity search
dynamism
metric spaces
non-conventional databases
description Metric space indices make searches for similar objects more efficient in various applications, including multimedia databases and other repositories which handle complex and unstructured objects. Although there are a plethora of indexes to speed up similarity searches, the Distal Spatial Approximation Tree (DiSAT) has shown to be very efficient and competitive. Nevertheless, for its construction, we need to know all the database objects beforehand, which is not necessarily possible in many real applications. The main drawback of the DiSAT is that it is a static data structure. That means, once built, it is difficult to insert new elements into it. This restriction rules it out for many exciting applications. In this paper, we overcome this weakness. We propose and study a dynamic version of DiSAT that allows handling lazy insertions and, at the same time, improves its good search performance. Therefore, our proposal provides a good tradeoff between construction cost, search cost, and space requirement. The result 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 Chávez, Edgar
Di Genaro, María E.
Reyes, Nora Susana
author_facet Chávez, Edgar
Di Genaro, María E.
Reyes, Nora Susana
author_sort Chávez, Edgar
title An Efficient Dynamic Version of the Distal Spatial Approximation Trees
title_short An Efficient Dynamic Version of the Distal Spatial Approximation Trees
title_full An Efficient Dynamic Version of the Distal Spatial Approximation Trees
title_fullStr An Efficient Dynamic Version of the Distal Spatial Approximation Trees
title_full_unstemmed An Efficient Dynamic Version of the Distal Spatial Approximation Trees
title_sort efficient dynamic version of the distal spatial approximation trees
publishDate 2022
url http://sedici.unlp.edu.ar/handle/10915/149651
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