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dc.contributor.author
Broz, Diego Ricardo
dc.contributor.author
Olivera, Alejandro
dc.contributor.author
Viana Céspedes, Víctor
dc.contributor.author
Rossit, Daniel Alejandro
dc.date.available
2021-08-11T23:10:23Z
dc.date.issued
2017
dc.identifier.citation
Review of Data mining applications in forestry sector; First International Conference on Agro Big Data and Decision Support Systems in Agriculture; Montevideo; Uruguay; 2017; 143-146
dc.identifier.uri
http://hdl.handle.net/11336/138182
dc.description.abstract
Modern technology makes possible to collect large amount of data that can be processed and transformed invaluable information for several human activities. Forest industry particularly can take advantage of suchtechnology because of modern forest harvesters are equipped with a system for data collection and communicationcalled StanForD. Data mining allows users to process large databases to determine trends and patterns. In thisextended abstract we present a brief revision of the literature dedicated to the issue and, also, we indicatesynthetically future research directions that could be useful for forest operations management. Some DMtechniques are artificial neural network and decision tree and they are used to perform association, classificationand clustering. Nonetheless, data mining techniques have been successfully applied to several fields, e.g. industry,marketing, sociology, economy, agriculture and environmental sciences.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Universidad de la República
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
BIG DATA
dc.subject
FOREST
dc.subject
REVIEW
dc.subject.classification
Otras Ingenierías y Tecnologías
dc.subject.classification
Otras Ingenierías y Tecnologías
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
dc.title
Review of Data mining applications in forestry sector
dc.type
info:eu-repo/semantics/publishedVersion
dc.type
info:eu-repo/semantics/conferenceObject
dc.type
info:ar-repo/semantics/documento de conferencia
dc.date.updated
2021-06-22T13:48:57Z
dc.journal.pagination
143-146
dc.journal.pais
Uruguay
dc.journal.ciudad
Montevideo
dc.description.fil
Fil: Broz, Diego Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Misiones. Facultad de Ciencias Forestales; Argentina
dc.description.fil
Fil: Olivera, Alejandro. Universidad de la República; Uruguay
dc.description.fil
Fil: Viana Céspedes, Víctor. Universidad de la República; Uruguay
dc.description.fil
Fil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina
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info:eu-repo/semantics/altIdentifier/url/http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=63228©ownerid=64337
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.bigdssagro.udl.cat/?q=node/75
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.bigdssagro.udl.cat/sites/default/files/Proceedings_bigDSSagro2017.pdf
dc.conicet.rol
Autor
dc.conicet.rol
Autor
dc.conicet.rol
Autor
dc.conicet.rol
Autor
dc.coverage
Internacional
dc.type.subtype
Conferencia
dc.description.nombreEvento
First International Conference on Agro Big Data and Decision Support Systems in Agriculture
dc.date.evento
2017-09-27
dc.description.ciudadEvento
Montevideo
dc.description.paisEvento
Uruguay
dc.type.publicacion
Book
dc.description.institucionOrganizadora
Universidad de la República
dc.source.libro
Proceedings of the First International Conference on Agro Big Data and Decision Support Systems in Agriculture
dc.date.eventoHasta
2017-09-29
dc.type
Conferencia
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