| |
|
|
 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
|
Registro Completo |
|
Biblioteca(s): |
Embrapa Agricultura Digital. |
|
Data corrente: |
23/12/2015 |
|
Data da última atualização: |
07/01/2020 |
|
Tipo da produção científica: |
Artigo em Anais de Congresso |
|
Autoria: |
CHINO, D. Y. T.; GONCALVES, R. R. V.; ROMANI, L. A. S.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. |
|
Afiliação: |
DANIEL Y. T.CHINO, ICMC/USP; RENATA R. V. GONCALVES, Cepagri/Unicamp; LUCIANA ALVIM SANTOS ROMANI, CNPTIA; CAETANO TRAINA JÚNIOR, ICMC/USP; AGMA J. M. TRAINA, ICMC/USP. |
|
Título: |
Discovering frequent patterns on agrometeorological data with TrieMotif. |
|
Ano de publicação: |
2015 |
|
Fonte/Imprenta: |
In: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 16., 2014, Lisbon. Enterprise information systems: ICEIS 2014: revised selected papers. Switzerland: Springer, 2015. |
|
Páginas: |
p. 91-107. |
|
Série: |
(Lecture notes in business information processing, 227). |
|
DOI: |
10.1007/978-3-319-22348-3 |
|
Idioma: |
Inglês |
|
Notas: |
Editores: José Cordeiro, Slimane Hammoudi, Leszek Maciaszek, Olivier Camp, Joaquim Filipe. |
|
Conteúdo: |
The "food safety" issue has concerned governments from several countries. The accurate monitoring of agriculture have become important specially due to climate change impacts. In this context, the development of new technologies for monitoring are crucial. Finding previously unknown patterns that frequently occur on time series, known as motifs, is a core task to mine the collected data. In this work we present a method that allows a fast and accurate time series motif discovery. From the experiments we can see that our approach is able to efficiently find motifs even when the size of the time series goes longer. We also evaluated our method using real data time series extracted from remote sensing images regarding sugarcane crops. Our proposed method was able to find relevant patterns, as sugarcane cycles and other land covers inside the same area, which are really useful for data analysis. |
|
Palavras-Chave: |
Dados agrometeorológicos; Frequent motif; Remote sensing image; Séries temporais. |
|
Thesagro: |
Análise de dados. |
|
Thesaurus Nal: |
Data analysis; Remote sensing; Time series analysis. |
|
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
|
Marc: |
LEADER 02051nam a2200301 a 4500
001 2032322
005 2020-01-07
008 2015 bl uuuu u00u1 u #d
024 7 $a10.1007/978-3-319-22348-3$2DOI
100 1 $aCHINO, D. Y. T.
245 $aDiscovering frequent patterns on agrometeorological data with TrieMotif.$h[electronic resource]
260 $aIn: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 16., 2014, Lisbon. Enterprise information systems: ICEIS 2014: revised selected papers. Switzerland: Springer$c2015
300 $ap. 91-107.
490 $a(Lecture notes in business information processing, 227).
500 $aEditores: José Cordeiro, Slimane Hammoudi, Leszek Maciaszek, Olivier Camp, Joaquim Filipe.
520 $aThe "food safety" issue has concerned governments from several countries. The accurate monitoring of agriculture have become important specially due to climate change impacts. In this context, the development of new technologies for monitoring are crucial. Finding previously unknown patterns that frequently occur on time series, known as motifs, is a core task to mine the collected data. In this work we present a method that allows a fast and accurate time series motif discovery. From the experiments we can see that our approach is able to efficiently find motifs even when the size of the time series goes longer. We also evaluated our method using real data time series extracted from remote sensing images regarding sugarcane crops. Our proposed method was able to find relevant patterns, as sugarcane cycles and other land covers inside the same area, which are really useful for data analysis.
650 $aData analysis
650 $aRemote sensing
650 $aTime series analysis
650 $aAnálise de dados
653 $aDados agrometeorológicos
653 $aFrequent motif
653 $aRemote sensing image
653 $aSéries temporais
700 1 $aGONCALVES, R. R. V.
700 1 $aROMANI, L. A. S.
700 1 $aTRAINA JÚNIOR, C.
700 1 $aTRAINA, A. J. M.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
|
| Registros recuperados : 11 | |
| 3. |  | CHINO, D. Y. T.; GONCALVES, R. R. V.; ROMANI, L. A. S.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. Discovering frequent patterns on agrometeorological data with TrieMotif. In: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 16., 2014, Lisbon. Enterprise information systems: ICEIS 2014: revised selected papers. Switzerland: Springer, 2015. p. 91-107. (Lecture notes in business information processing, 227). Editores: José Cordeiro, Slimane Hammoudi, Leszek Maciaszek, Olivier Camp, Joaquim Filipe.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
|    |
| 5. | | CHINO, D. Y. T.; GONÇALVES, R. R. V.; ROMANI, L. A. S.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. TrieMotif: a new and efficient method to mine frequent K-motifs from large time series. In: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 16.; INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING, 9., 2014, Lisbon. Proceedings... [S.l.]: Scitepress, 2014. p. 60-69. ICEIS 2014.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| 6. | | AMARAL, B. F.; CHINO, D. Y.; ROMANI, L. A. S.; GONÇALVES, R. R. V.; SOUSA, E. P. M. de; TRAINA, A. J. M. Análise e mineração de dados de sensores orbitais para acompanhamento de safras de cana-de-açúcar. In: CONGRESSO DA SOCIEDADE BRASILEIRA DE COMPUTAÇÃO, 31; WORKSHOP DE COMPUTAÇÃO APLICADA À GESTÃO DO MEIO AMBIENTE E RECURSOS NATURAIS, 3., 2011, Natal. Computação para todos: no caminho da evolução social: anais. Natal: UFRN, 2O11. p. 1472-1481. WCAMA 2011.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
|  |
| 7. | | ROMANI, L. A. S.; CHINO, D. Y. T.; AVALHAIS, L. P. S.; OLIVEIRA, W. D.; GONÇALVES, R. R. V.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. Involving users in the gestural language definition process for the NInA framework. In: BRAZILIAN SYMPOSIUM ON HUMAN FACTORS IN COMPUTING SYSTEMS, 12., 2013, Manaus. Proceedings... Porto Alegre: SBC, 2013. p. 280-283. IHC 2013.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| 8. | | ROMANI, L. A. S.; AVILA, A. M. H. de; CHINO, D. Y. T.; ZULLO JÚNIOR, J.; CHBEIR, R.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. A new time series mining approach applied to multitemporal remote sensing imagery. IEEE transactions on geoscience and remote sensing, New York, v. 51, n. 1, p. 140-150, Jan. 2013.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| 9. | | CHINO, D. Y. T.; ROMANI, L. A. S.; AVALHAIS, L. P. S.; OLIVEIRA, W. D.; GONÇALVES, R. R. V.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. The NInA Framework using gesture to improve interaction and collaboration in geographical information systems. In: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 15.; INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING, 8., 2013, Angers Loire Valley. Proceedings... [S.l.]: Scitepress, 2013. p. 35-43. ICEIS 2013. ENASE 2013.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| 10. | | AMARAL, B. F.; CHINO, D. Y. T.; ROMANI, L. A. S.; GONÇALVES, R. R. V.; TRAINA, A. J. M.; SOUSA, E. P. M. The SITSMining framework: a data mining approach for satellite image time series. In: INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, 16.; INTERNATIONAL CONFERENCE ON EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING, 9., 2014, Lisbon. Proceedings... [S.l.]: Scitepress, 2014. p. 225-232. ICEIS 2014.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| 11. | | ROMANI, L. A. S.; GONÇALVES, R. R. V.; AMARAL, B. F.; CHINO, D. Y. T.; ZULLO JUNIOR, J.; TRAINA JUNIOR, C.; SOUSA, E. P. M.; TRAINA, A. J. M. TRAINA. Clustering analysis applied to NOAA/AVHRR multitemporal images to improve the monitoring process of sugarcane crops. In: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTI-TEMPORAL REMOTE SENSING IMAGES, 6., 2011, Trento. Proceedings... Piscataway: IEEE; Italy: University of Trento, 2011. p. 33-36.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| Registros recuperados : 11 | |
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
