Quality data extraction methodology based on the labeling of coffee leaves with nutritional deficiencies

Descripción del Articulo

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
Detalles Bibliográficos
Autores: Jungbluth, Adolfo, Yeng, Jon Li
Formato: artículo
Fecha de Publicación:2018
Institución:Universidad Peruana de Ciencias Aplicadas
Repositorio:UPC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorioacademico.upc.edu.pe:10757/624685
Enlace del recurso:http://hdl.handle.net/10757/624685
Nivel de acceso:acceso embargado
Materia:Data extraction
Data quality assessment
Quality data extraction methodology
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dc.title.en_US.fl_str_mv Quality data extraction methodology based on the labeling of coffee leaves with nutritional deficiencies
title Quality data extraction methodology based on the labeling of coffee leaves with nutritional deficiencies
spellingShingle Quality data extraction methodology based on the labeling of coffee leaves with nutritional deficiencies
Jungbluth, Adolfo
Data extraction
Data quality assessment
Quality data extraction methodology
title_short Quality data extraction methodology based on the labeling of coffee leaves with nutritional deficiencies
title_full Quality data extraction methodology based on the labeling of coffee leaves with nutritional deficiencies
title_fullStr Quality data extraction methodology based on the labeling of coffee leaves with nutritional deficiencies
title_full_unstemmed Quality data extraction methodology based on the labeling of coffee leaves with nutritional deficiencies
title_sort Quality data extraction methodology based on the labeling of coffee leaves with nutritional deficiencies
author Jungbluth, Adolfo
author_facet Jungbluth, Adolfo
Yeng, Jon Li
author_role author
author2 Yeng, Jon Li
author2_role author
dc.contributor.email.es_PE.fl_str_mv U201311506@upc.edu.pe
dc.contributor.author.fl_str_mv Jungbluth, Adolfo
Yeng, Jon Li
dc.subject.en_US.fl_str_mv Data extraction
Data quality assessment
Quality data extraction methodology
topic Data extraction
Data quality assessment
Quality data extraction methodology
description El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
publishDate 2018
dc.date.accessioned.none.fl_str_mv 2018-11-29T15:12:55Z
dc.date.available.none.fl_str_mv 2018-11-29T15:12:55Z
dc.date.issued.fl_str_mv 2018-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
dc.type.version.none.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a2598
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dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10757/624685
dc.identifier.journal.en_US.fl_str_mv ACM International Conference Proceeding Series
dc.identifier.isni.none.fl_str_mv 0000 0001 2196 144X
url http://hdl.handle.net/10757/624685
identifier_str_mv ACM International Conference Proceeding Series
0000 0001 2196 144X
dc.language.iso.en_US.fl_str_mv eng
language eng
dc.rights.en_US.fl_str_mv info:eu-repo/semantics/embargoedAccess
eu_rights_str_mv embargoedAccess
dc.publisher.en_US.fl_str_mv Association for Computing Machinery
dc.source.none.fl_str_mv reponame:UPC-Institucional
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spelling c633988266b31c951199c744c951838e-181aa9f9b0c297853ccebad00360e9d4b-1Jungbluth, AdolfoYeng, Jon LiU201311506@upc.edu.pe2018-11-29T15:12:55Z2018-11-29T15:12:55Z2018-04http://hdl.handle.net/10757/624685ACM International Conference Proceeding Series0000 0001 2196 144XEl texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.Nutritional deficiencies detection for coffee leaves is a task which is often undertaken manually by experts on the field known as agronomists. The process they follow to carry this task is based on observation of the different characteristics of the coffee leaves while relying on their own experience. Visual fatigue and human error in this empiric approach cause leaves to be incorrectly labeled and thus affecting the quality of the data obtained. In this context, different crowdsourcing approaches can be applied to enhance the quality of the data extracted. These approaches separately propose the use of voting systems, association rule filters and evolutive learning. In this paper, we extend the use of association rule filters and evolutive approach by combining them in a methodology to enhance the quality of the data while guiding the users during the main stages of data extraction tasks. Moreover, our methodology proposes a reward component to engage users and keep them motivated during the crowdsourcing tasks. The extracted dataset by applying our proposed methodology in a case study on Peruvian coffee leaves resulted in 93.33% accuracy with 30 instances collected by 8 experts and evaluated by 2 agronomic engineers with background on coffee leaves. The accuracy of the dataset was higher than independently implementing the evolutive feedback strategy and an empiric approach which resulted in 86.67% and 70% accuracy respectively under the same conditions.Revisión por paresengAssociation for Computing Machineryinfo:eu-repo/semantics/embargoedAccessData extractionData quality assessmentQuality data extraction methodologyQuality data extraction methodology based on the labeling of coffee leaves with nutritional deficienciesinfo:eu-repo/semantics/articlehttp://purl.org/coar/version/c_970fb48d4fbd8a2598reponame:UPC-Institucionalinstname:Universidad Peruana de Ciencias Aplicadasinstacron:UPC2018-11-29T15:14:36ZTHUMBNAIL10.1145 3206098.3206102.pdf.jpg10.1145 3206098.3206102.pdf.jpgGenerated Thumbnailimage/jpeg78438https://repositorioacademico.upc.edu.pe/bitstream/10757/624685/4/10.1145%203206098.3206102.pdf.jpg250dd88c9a552964828c0b4d9440fa8aMD54falseTEXT10.1145 3206098.3206102.pdf.txt10.1145 3206098.3206102.pdf.txtExtracted texttext/plain2950https://repositorioacademico.upc.edu.pe/bitstream/10757/624685/3/10.1145%203206098.3206102.pdf.txte190f92c690ee3665ed1ef0ed90d228cMD53falseORIGINAL10.1145 3206098.3206102.pdf10.1145 3206098.3206102.pdfapplication/pdf109675https://repositorioacademico.upc.edu.pe/bitstream/10757/624685/2/10.1145%203206098.3206102.pdfad4f0b0568cfdb82355fff4f0d26e57cMD52trueLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorioacademico.upc.edu.pe/bitstream/10757/624685/1/license.txt8a4605be74aa9ea9d79846c1fba20a33MD51false10757/624685oai:repositorioacademico.upc.edu.pe:10757/6246852026-02-17 17:49:01.411Repositorio Académico UPCupc@openrepository.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Quality data extraction methodology based on the labeling of coffee leaves with nutritional deficiencies
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