Big data aplication for selecting theses topics

Aplicación de Big Data para seleccionar estos temas.

dc.creatorSilva, Jesus
dc.creatorHernandez, Lissette
dc.creatorCrissien Borrero, Tito José
dc.creatorPineda Lezama, Omar Bonerge
dc.creatorRomero Melo, Jenny Esperanza
dc.date2020-02-05T13:28:23Z
dc.date2020-02-05T13:28:23Z
dc.date2019
dc.date.accessioned2023-10-03T19:09:03Z
dc.date.available2023-10-03T19:09:03Z
dc.identifier00002010
dc.identifierhttp://hdl.handle.net/11323/5988
dc.identifierCorporación Universidad de la Costa
dc.identifierREDICUC - Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9168247
dc.descriptionThe chairs of thesis research in Computer Sciences at the University of Mumbai, in India, have different tools that provide academic support to those who begin the course. Students present difficulty in selecting the topic to study and, in some cases, this is a reason to neglect or delay in the career. Having a registry of thesis of the graduates proved to be useful for obtaining patterns on the relationship between the research area addressed in this thesis and the characteristics that define the researcher. For this study, the knowledge discovery process in Database was used. Finally, the results of the use of algorithms J4.8 in WEKA, ID3 tags in RapidMiner and CART IN Knime and the various models generated, with the data collected were presented.
dc.descriptionLos presidentes de investigación de tesis en Ciencias de la Computación de la Universidad de Mumbai, en India, tienen diferentes herramientas que brindan apoyo académico a quienes comienzan el curso. Los estudiantes presentan dificultades para seleccionar el tema a estudiar y, en algunos casos, esta es una razón para descuidar o retrasar la carrera. Tener un registro de tesis de los graduados demostró ser útil para obtener patrones sobre la relación entre el área de investigación abordada en esta tesis y las características que definen al investigador. Para este estudio, se utilizó el proceso de descubrimiento de conocimiento en la base de datos. Finalmente, se presentaron los resultados del uso de algoritmos J4.8 en WEKA, etiquetas ID3 en RapidMiner y CART IN Knime y los diversos modelos generados, con los datos recopilados.
dc.formatapplication/pdf
dc.languageeng
dc.publisherProcedia Computer Science
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dc.rightsCC0 1.0 Universal
dc.rightshttp://creativecommons.org/publicdomain/zero/1.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subjectDecision trees
dc.subjectWEKA
dc.subjectRapidMiner
dc.subjectKnime
dc.subjectAreas of research
dc.subjectÁrboles de decisión
dc.subjectRapidMiner
dc.subjectÁreas de investigación
dc.titleBig data aplication for selecting theses topics
dc.titleAplicación de Big Data para seleccionar estos temas.
dc.typeArtículo de revista
dc.typehttp://purl.org/coar/resource_type/c_6501
dc.typeText
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/submittedVersion
dc.typehttp://purl.org/redcol/resource_type/ART
dc.typeinfo:eu-repo/semantics/acceptedVersion
dc.typehttp://purl.org/coar/version/c_ab4af688f83e57aa


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