Combining methods for searches in nested metric spaces

Most search methods in metric spaces assume that the topology of the object collection is reasonably regular. However, there exist nested metric spaces, where objects in the collection can be grouped into clusters or subspaces, in such a way that different dimensions or variables explain the differe...

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Detalles Bibliográficos
Autores principales:	Gercek, Hugo, Reyes, Nora Susana, Deco, Claudia, Bender, Cristina, Salvetti, Mariano
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	2011
Materias:	Ciencias Informáticas metric spaces; pivots selection; similarity search
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/18751
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-18751
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 metric spaces; pivots selection; similarity search
spellingShingle	Ciencias Informáticas metric spaces; pivots selection; similarity search Gercek, Hugo Reyes, Nora Susana Deco, Claudia Bender, Cristina Salvetti, Mariano Combining methods for searches in nested metric spaces
topic_facet	Ciencias Informáticas metric spaces; pivots selection; similarity search
description	Most search methods in metric spaces assume that the topology of the object collection is reasonably regular. However, there exist nested metric spaces, where objects in the collection can be grouped into clusters or subspaces, in such a way that different dimensions or variables explain the differences between objects inside each subspace. This paper proposes a two levels index to solve search problems in spaces with this topology. The idea is to have a first level with a list of clusters, which are identified and sorted using Sparse Spatial Selection (SSS) and Lists of Clusters techniques, and a second level having an index for each dense cluster, based on pivot selection, using SSS. It is also proposed for future work to adjust the second level indexes through dynamic pivots selection to adapt the pivots according to the searches performed in the database.
format	Objeto de conferencia Objeto de conferencia
author	Gercek, Hugo Reyes, Nora Susana Deco, Claudia Bender, Cristina Salvetti, Mariano
author_facet	Gercek, Hugo Reyes, Nora Susana Deco, Claudia Bender, Cristina Salvetti, Mariano
author_sort	Gercek, Hugo
title	Combining methods for searches in nested metric spaces
title_short	Combining methods for searches in nested metric spaces
title_full	Combining methods for searches in nested metric spaces
title_fullStr	Combining methods for searches in nested metric spaces
title_full_unstemmed	Combining methods for searches in nested metric spaces
title_sort	combining methods for searches in nested metric spaces
publishDate	2011
url	http://sedici.unlp.edu.ar/handle/10915/18751
work_keys_str_mv	AT gercekhugo combiningmethodsforsearchesinnestedmetricspaces AT reyesnorasusana combiningmethodsforsearchesinnestedmetricspaces AT decoclaudia combiningmethodsforsearchesinnestedmetricspaces AT bendercristina combiningmethodsforsearchesinnestedmetricspaces AT salvettimariano combiningmethodsforsearchesinnestedmetricspaces
bdutipo_str	Repositorios
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Combining methods for searches in nested metric spaces

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