Adaptive Ttwo-phase spatial association rules mining method

Since huge amounts of spatial data can be easily collected from various applications, ranging from remote sensing technology to geographical information system, the extraction and comprehension of spatial knowledge is a more and more important task. Many excellent studies on Remote Sensed Image (RSI...

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Detalles Bibliográficos
Autores principales:	Lee, Chin-Feng, Chen, Mei-Hsiu
Formato:	Articulo
Lenguaje:	Inglés
Publicado:	2006
Materias:	Ciencias Informáticas remote sensed image Data mining Spatial databases and GIS
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/9516 http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr06-6.pdf
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-9516
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 remote sensed image Data mining Spatial databases and GIS
spellingShingle	Ciencias Informáticas remote sensed image Data mining Spatial databases and GIS Lee, Chin-Feng Chen, Mei-Hsiu Adaptive Ttwo-phase spatial association rules mining method
topic_facet	Ciencias Informáticas remote sensed image Data mining Spatial databases and GIS
description	Since huge amounts of spatial data can be easily collected from various applications, ranging from remote sensing technology to geographical information system, the extraction and comprehension of spatial knowledge is a more and more important task. Many excellent studies on Remote Sensed Image (RSI) have been conducted for potential relationships of crop yield. However, most of them suffer from the performance problem because their techniques for mining association rules are based on Apriori algorithm. In this paper, two efficient algorithms, two-phase spatial association rules mining and adaptive two-phase spatial association rules mining, are proposed for address the above problem. Both methods primarily conduct two phase algorithms by creating Histogram Generators for fast generating coarse-grained spatial association rules, and further mining the fine-grained spatial association rules w.r.t the coarse-grained frequently patterns obtained in the first phase. Adaptive two-phase spatial association rules mining method conducts the idea of partition on an image for efficiently quantizing out non-frequent patterns and thus facilitate the following two phase process. Such two-phase approaches save much computations and will be shown by lots of experimental results in the paper.
format	Articulo Articulo
author	Lee, Chin-Feng Chen, Mei-Hsiu
author_facet	Lee, Chin-Feng Chen, Mei-Hsiu
author_sort	Lee, Chin-Feng
title	Adaptive Ttwo-phase spatial association rules mining method
title_short	Adaptive Ttwo-phase spatial association rules mining method
title_full	Adaptive Ttwo-phase spatial association rules mining method
title_fullStr	Adaptive Ttwo-phase spatial association rules mining method
title_full_unstemmed	Adaptive Ttwo-phase spatial association rules mining method
title_sort	adaptive ttwo-phase spatial association rules mining method
publishDate	2006
url	http://sedici.unlp.edu.ar/handle/10915/9516 http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr06-6.pdf
work_keys_str_mv	AT leechinfeng adaptivettwophasespatialassociationrulesminingmethod AT chenmeihsiu adaptivettwophasespatialassociationrulesminingmethod
bdutipo_str	Repositorios
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Adaptive Ttwo-phase spatial association rules mining method

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