Una revisión sistemática de problemas de calidad en los datos en tareas de descubrimiento de conocimiento
Hay un gran crecimiento en el volumen de datos porque las organizaciones capturan permanentemente la cantidad colectiva de datos para lograr un mejor proceso de toma de decisiones. El desafío mas fundamental es la exploración de los grandes volúmenes de datos y la extracción de conocimiento útil par...
- Autores:
-
Corrales, David Camilo
Ledezma, Agapito Ismael
Corrales, Juan Carlos
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2016
- Institución:
- Universidad de Medellín
- Repositorio:
- Repositorio UDEM
- Idioma:
- eng
- OAI Identifier:
- oai:repository.udem.edu.co:11407/3550
- Acceso en línea:
- http://hdl.handle.net/11407/3550
- Palabra clave:
- Heterogeneity
Outliers
noise
Inconsistency
Incompleteness
Amount of data
Redundancy
Timeliness
Heterogeneidad
Valores atípicos
Ruido
Inconsistencia
Valores perdidos
Cantidad de datos
Redundancia
Oportunidad
- Rights
- License
- http://creativecommons.org/licenses/by-nc-sa/4.0/
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Una revisión sistemática de problemas de calidad en los datos en tareas de descubrimiento de conocimiento A systematic review of data quality issues in knowledge discovery tasks |
| title |
Una revisión sistemática de problemas de calidad en los datos en tareas de descubrimiento de conocimiento |
| spellingShingle |
Una revisión sistemática de problemas de calidad en los datos en tareas de descubrimiento de conocimiento Heterogeneity Outliers noise Inconsistency Incompleteness Amount of data Redundancy Timeliness Heterogeneidad Valores atípicos Ruido Inconsistencia Valores perdidos Cantidad de datos Redundancia Oportunidad |
| title_short |
Una revisión sistemática de problemas de calidad en los datos en tareas de descubrimiento de conocimiento |
| title_full |
Una revisión sistemática de problemas de calidad en los datos en tareas de descubrimiento de conocimiento |
| title_fullStr |
Una revisión sistemática de problemas de calidad en los datos en tareas de descubrimiento de conocimiento |
| title_full_unstemmed |
Una revisión sistemática de problemas de calidad en los datos en tareas de descubrimiento de conocimiento |
| title_sort |
Una revisión sistemática de problemas de calidad en los datos en tareas de descubrimiento de conocimiento |
| dc.creator.fl_str_mv |
Corrales, David Camilo Ledezma, Agapito Ismael Corrales, Juan Carlos |
| dc.contributor.author.none.fl_str_mv |
Corrales, David Camilo Ledezma, Agapito Ismael Corrales, Juan Carlos |
| dc.subject.spa.fl_str_mv |
Heterogeneity Outliers noise Inconsistency Incompleteness Amount of data Redundancy Timeliness Heterogeneidad Valores atípicos Ruido Inconsistencia Valores perdidos Cantidad de datos Redundancia Oportunidad |
| topic |
Heterogeneity Outliers noise Inconsistency Incompleteness Amount of data Redundancy Timeliness Heterogeneidad Valores atípicos Ruido Inconsistencia Valores perdidos Cantidad de datos Redundancia Oportunidad |
| description |
Hay un gran crecimiento en el volumen de datos porque las organizaciones capturan permanentemente la cantidad colectiva de datos para lograr un mejor proceso de toma de decisiones. El desafío mas fundamental es la exploración de los grandes volúmenes de datos y la extracción de conocimiento útil para futuras acciones por medio de tareas para el descubrimiento del conocimiento; sin embargo, muchos datos presentan mala calidad. Presentamos una revisión sistemática de los asuntos de calidad de datos en las áreas del descubrimiento de conocimiento y un estudio de caso aplicado a la enfermedad agrícola conocida como la roya del café. |
| publishDate |
2016 |
| dc.date.created.none.fl_str_mv |
2016-06-30 |
| dc.date.accessioned.none.fl_str_mv |
2017-06-29T22:22:36Z |
| dc.date.available.none.fl_str_mv |
2017-06-29T22:22:36Z |
| dc.type.eng.fl_str_mv |
Article |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
| dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| dc.type.coar.none.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
| dc.type.local.spa.fl_str_mv |
Artículo científico |
| dc.type.driver.none.fl_str_mv |
info:eu-repo/semantics/article |
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http://purl.org/coar/resource_type/c_6501 |
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1692-3324 |
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http://hdl.handle.net/11407/3550 |
| dc.identifier.doi.none.fl_str_mv |
http://dx.doi.org/10.22395/rium.v15n28a7 |
| dc.identifier.eissn.none.fl_str_mv |
2248-4094 |
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reponame:Repositorio Institucional Universidad de Medellín |
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repourl:https://repository.udem.edu.co/ |
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instname:Universidad de Medellín |
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1692-3324 http://dx.doi.org/10.22395/rium.v15n28a7 2248-4094 reponame:Repositorio Institucional Universidad de Medellín repourl:https://repository.udem.edu.co/ instname:Universidad de Medellín |
| url |
http://hdl.handle.net/11407/3550 |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.uri.none.fl_str_mv |
http://revistas.udem.edu.co/index.php/ingenierias/article/view/1066 |
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15 |
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28 |
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125 |
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150 |
| dc.relation.references.spa.fl_str_mv |
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Technics Publications, 2007. J. Debenham, “Knowledge Decay in a Normalised Knowledge Base,” in Database and Expert Systems Applications, M. Ibrahim, J. Küng, and N. Revell, Eds. Springer Berlin Heidelberg, 2000, pp. 417-426. G. Cormode, V. Shkapenyuk, D. Srivastava, and B. Xu, “Forward Decay: A Practical Time Decay Model for Streaming Systems,” in Proceedings of the 2009 IEEE International Conference on Data Engineering, Washington, DC, USA, 2009, pp. 138-149. M. Placide and Y. Lasheng, “Information Decay in Building Predictive Models Using Temporal Data,” in 2010 International Symposium on Information Science and Engineering (ISISE), 2010, pp. 458-462. M. E. Cintra, C. A. A. Meira, M. C. Monard, H. A. Camargo, and L. H. A. Rodrigues, “The use of fuzzy decision trees for coffee rust warning in Brazilian crops,” in 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA), 2011, pp. 1347-1352. D. C. Corrales, A. J. P. Q, C. León, A. Figueroa, and J. C. Corrales, “Early warning system for coffee rust disease based on error correcting output codes: a proposal,” Rev. Ing. Univ. Medellín, vol. 13, no. 25, 2014. D. C. Corrales, A. Ledezma, A. J. P. Q, J. Hoyos, A. Figueroa, and J. C. Corrales, “A new dataset for coffee rust detection in Colombian crops base on classifiers,” Sist. Telemática, vol. 12, no. 29, pp. 9-23, Jun. 2014. D. C. C. Corrales, J. C. Corrales, and A. Figueroa-Casas, “Toward detecting crop diseases and pest by supervised learning,” Ing. Univ., vol. 19, no. 1, 2015. D. C. Corrales, A. Figueroa, A. Ledezma, and J. C. Corrales, “An Empirical Multi-classifier for Coffee Rust Detection in Colombian Crops,” in Computational Science and Its Applications -- ICCSA 2015, O. Gervasi, B. Murgante, S. Misra, M. L. Gavrilova, A. M. A. C. Rocha, C. Torre, D. Taniar, and B. O. Apduhan, Eds. Springer International Publishing, 2015, pp. 60-74. |
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Corrales, David CamiloLedezma, Agapito IsmaelCorrales, Juan CarlosCorrales, David Camilo; Universidad del Cauca - Universidad Carlos III de MadridLedezma, Agapito Ismael; Universidad Carlos III de MadridCorrales, Juan Carlos2017-06-29T22:22:36Z2017-06-29T22:22:36Z2016-06-301692-3324http://hdl.handle.net/11407/3550 http://dx.doi.org/10.22395/rium.v15n28a72248-4094reponame:Repositorio Institucional Universidad de Medellínrepourl:https://repository.udem.edu.co/instname:Universidad de MedellínHay un gran crecimiento en el volumen de datos porque las organizaciones capturan permanentemente la cantidad colectiva de datos para lograr un mejor proceso de toma de decisiones. El desafío mas fundamental es la exploración de los grandes volúmenes de datos y la extracción de conocimiento útil para futuras acciones por medio de tareas para el descubrimiento del conocimiento; sin embargo, muchos datos presentan mala calidad. Presentamos una revisión sistemática de los asuntos de calidad de datos en las áreas del descubrimiento de conocimiento y un estudio de caso aplicado a la enfermedad agrícola conocida como la roya del café.Large volume of data is growing because the organizations are continuously capturing the collective amount of data for better decision-making process. The most fundamental challenge is to explore the large volumes of data and extract useful knowledge for future actions through knowledge discovery tasks, nevertheless many data has poor quality. We presented a systematic review of the data quality issues in knowledge discovery tasks and a case study applied to agricultural disease named coffee rust.p. 125-150Electrónicoapplication/pdfengUniversidad de MedellínFacultad de IngenieríasMedellínhttp://revistas.udem.edu.co/index.php/ingenierias/article/view/10661528125150J. 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Springer International Publishing, 2015, pp. 60-74.Revista Ingenierías Universidad de Medellínhttp://creativecommons.org/licenses/by-nc-sa/4.0/Attribution-NonCommercial-ShareAlike 4.0 Internationalhttp://purl.org/coar/access_right/c_abf2Revista Ingenierías Universidad de Medellín; Vol. 15, núm. 28 (2016)2248-40941692-3324HeterogeneityOutliersnoiseInconsistencyIncompletenessAmount of dataRedundancyTimelinessHeterogeneidadValores atípicosRuidoInconsistenciaValores perdidosCantidad de datosRedundanciaOportunidadUna revisión sistemática de problemas de calidad en los datos en tareas de descubrimiento de conocimientoA systematic review of data quality issues in knowledge discovery tasksArticlehttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Artículo científicoinfo:eu-repo/semantics/articlehttp://purl.org/coar/version/c_970fb48d4fbd8a85Comunidad Universidad de MedellínLat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degreesLong: 075 36 00 W degrees minutes Long: -75.6000 decimal degreesTHUMBNAILRevista_Ingenierias_UdeM_277.pdf.jpgRevista_Ingenierias_UdeM_277.pdf.jpgIM Thumbnailimage/jpeg7204http://repository.udem.edu.co/bitstream/11407/3550/3/Revista_Ingenierias_UdeM_277.pdf.jpgee4199aa9bd9873b6af7bb0ad40f64ffMD53ORIGINALArticulo.htmltext/html497http://repository.udem.edu.co/bitstream/11407/3550/1/Articulo.html4807fedbf2fd1bd99750d44b3cb5e466MD51Revista_Ingenierias_UdeM_277.pdfRevista_Ingenierias_UdeM_277.pdfapplication/pdf1810323http://repository.udem.edu.co/bitstream/11407/3550/2/Revista_Ingenierias_UdeM_277.pdfd9dc4208c6eefe798bf1213569e887abMD5211407/3550oai:repository.udem.edu.co:11407/35502021-05-14 14:28:18.834Repositorio Institucional Universidad de Medellinrepositorio@udem.edu.co |