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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
05/01/2016 |
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Data da última atualização: |
21/01/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
BONES, C. C.; ROMANI, L. A. S.; SOUSA, E. P. M. de. |
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Afiliação: |
CHRISTIAN C. BONES, USP, São Carlos, SP; LUCIANA ALVIM SANTOS ROMANI, CNPTIA; ELAINE P. M. DE SOUSA, USP, São Carlos, SP. |
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Título: |
Clustering multivariate climate data streams using fractal dimension. |
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Ano de publicação: |
2015 |
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Fonte/Imprenta: |
In: BRAZILIAN SYMPOSIUM ON DATABASES, 30., 2015, Petrópolis. Proceedings... Petrópolis: Laboratório Nacional de Computação Científica, 2015. |
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Páginas: |
p. 41-52. |
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Idioma: |
Inglês |
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Notas: |
SBBD 2015. |
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Conteúdo: |
Abstract. A data stream is a flow of data produced continuously along the time. Storing and analyzing such information become challenging due to exponential growth of the data volume collected. In this context, some methods were proposed to cluster data streams with similar behavior along the time. However, those methods have failed on clustering data flows with more than one attribute, i.e., multivariate flows. This paper introduces a new method to cluster multivariate data streams, based on fractal dimension, reading the data only once. We evaluated our method over real multivariate data streams generated by climate sensors. Not only was our method able to cluster the flows of data, but also identified sensors with similar behavior during the analyzed period. |
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Palavras-Chave: |
Análise multivariada; Banco de dados; Dimensão fractal. |
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Thesagro: |
Clima. |
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Thesaurus NAL: |
Cluster analysis; Databases; Fractal dimensions; Multivariate analysis. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
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001 2032974
005 2020-01-21
008 2015 bl uuuu u00u1 u #d
100 1 $aBONES, C. C.
245 $aClustering multivariate climate data streams using fractal dimension.$h[electronic resource]
260 $aIn: BRAZILIAN SYMPOSIUM ON DATABASES, 30., 2015, Petrópolis. Proceedings... Petrópolis: Laboratório Nacional de Computação Científica$c2015
300 $ap. 41-52.
500 $aSBBD 2015.
520 $aAbstract. A data stream is a flow of data produced continuously along the time. Storing and analyzing such information become challenging due to exponential growth of the data volume collected. In this context, some methods were proposed to cluster data streams with similar behavior along the time. However, those methods have failed on clustering data flows with more than one attribute, i.e., multivariate flows. This paper introduces a new method to cluster multivariate data streams, based on fractal dimension, reading the data only once. We evaluated our method over real multivariate data streams generated by climate sensors. Not only was our method able to cluster the flows of data, but also identified sensors with similar behavior during the analyzed period.
650 $aCluster analysis
650 $aDatabases
650 $aFractal dimensions
650 $aMultivariate analysis
650 $aClima
653 $aAnálise multivariada
653 $aBanco de dados
653 $aDimensão fractal
700 1 $aROMANI, L. A. S.
700 1 $aSOUSA, E. P. M. de
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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