SCi-XP: a Simple and Autoral Tool for Joining Artificial Intelligence to Non-Familiar People; Metrics and Visualization Performance for Unidimensional Time Series.

Detalhes bibliográficos
Autor(a) principal: Mota de Lacerda Padilha Schettini, Gabriela
Data de Publicação: 2020
Outros Autores: Salgado Gomes de Mattos Neto, Paulo
Tipo de documento: Artigo
Idioma: por
Título da fonte: Revista de Engenharia e Pesquisa Aplicada
Texto Completo: http://revistas.poli.br/index.php/repa/article/view/1339
Resumo: In this fast development world it is common to hear in academic environments about new tools for extracting information out of data. Unfortunately these tools that exists are made for people with previous knowledge of computer programming or coding, and in some way it excludes a little science from the practical field. Given the amount of technical tools for information mining this paper proposes a tool as an attempt of trying to join this both worlds that sometimes seems to be so distant  to a single website for prototyping time series forecasting models, to people with little to no knowledge of programming, in instants.
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spelling SCi-XP: a Simple and Autoral Tool for Joining Artificial Intelligence to Non-Familiar People; Metrics and Visualization Performance for Unidimensional Time Series.SCi-XP: uma Ferramenta Simples e Autoral para Previsão Séries Temporais com Foco na Experimentação para Pessoas não Familiares a Inteligência Artificial.In this fast development world it is common to hear in academic environments about new tools for extracting information out of data. Unfortunately these tools that exists are made for people with previous knowledge of computer programming or coding, and in some way it excludes a little science from the practical field. Given the amount of technical tools for information mining this paper proposes a tool as an attempt of trying to join this both worlds that sometimes seems to be so distant  to a single website for prototyping time series forecasting models, to people with little to no knowledge of programming, in instants.Diversas ferramentas de extração de informações de dados baseadas em Inteligência Artificial (IA) têm sido desenvolvidas. Contudo, a necessidade de programar ou de prototipar um código para um teste rápido faz com que pesquisadores com pouco, ou nenhum conhecimento em programação evitem utilizar técnicas de Inteligência Artificial. Este trabalho propõe uma ferramenta simples em formato de website com o objetivo de introduzir conceitos e modelos de Inteligência Artificial na tarefa de previsão de séries temporais a pessoas com pouco conhecimento em programação. A ferramenta visa tornar a IA uma área mais atraente para pesquisadores de outros ramos do conhecimento.Escola Politécnica de Pernambuco2020-04-30info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAvaliado pelos paresapplication/pdftext/htmlhttp://revistas.poli.br/index.php/repa/article/view/133910.25286/repa.v5i2.1339Journal of Engineering and Applied Research; Vol 5 No 2 (2020): Edição Especial em Inteligência Artificial; 36-43Revista de Engenharia e Pesquisa Aplicada; v. 5 n. 2 (2020): Edição Especial em Inteligência Artificial; 36-432525-425110.25286/repa.v5i2reponame:Revista de Engenharia e Pesquisa Aplicadainstname:Universidade Federal de Pernambuco (UFPE)instacron:UFPEporhttp://revistas.poli.br/index.php/repa/article/view/1339/611http://revistas.poli.br/index.php/repa/article/view/1339/612Copyright (c) 2020 Gabriela Mota de Lacerda Padilha Schettini, Paulo Salgado Gomes de Mattos Netohttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessMota de Lacerda Padilha Schettini, GabrielaSalgado Gomes de Mattos Neto, Paulo2021-07-13T08:41:02Zoai:ojs.poli.br:article/1339Revistahttp://revistas.poli.br/index.php/repaONGhttp://revistas.poli.br/index.php/repa/oai||repa@poli.br2525-42512525-4251opendoar:2021-07-13T08:41:02Revista de Engenharia e Pesquisa Aplicada - Universidade Federal de Pernambuco (UFPE)false
dc.title.none.fl_str_mv SCi-XP: a Simple and Autoral Tool for Joining Artificial Intelligence to Non-Familiar People; Metrics and Visualization Performance for Unidimensional Time Series.
SCi-XP: uma Ferramenta Simples e Autoral para Previsão Séries Temporais com Foco na Experimentação para Pessoas não Familiares a Inteligência Artificial.
title SCi-XP: a Simple and Autoral Tool for Joining Artificial Intelligence to Non-Familiar People; Metrics and Visualization Performance for Unidimensional Time Series.
spellingShingle SCi-XP: a Simple and Autoral Tool for Joining Artificial Intelligence to Non-Familiar People; Metrics and Visualization Performance for Unidimensional Time Series.
Mota de Lacerda Padilha Schettini, Gabriela
title_short SCi-XP: a Simple and Autoral Tool for Joining Artificial Intelligence to Non-Familiar People; Metrics and Visualization Performance for Unidimensional Time Series.
title_full SCi-XP: a Simple and Autoral Tool for Joining Artificial Intelligence to Non-Familiar People; Metrics and Visualization Performance for Unidimensional Time Series.
title_fullStr SCi-XP: a Simple and Autoral Tool for Joining Artificial Intelligence to Non-Familiar People; Metrics and Visualization Performance for Unidimensional Time Series.
title_full_unstemmed SCi-XP: a Simple and Autoral Tool for Joining Artificial Intelligence to Non-Familiar People; Metrics and Visualization Performance for Unidimensional Time Series.
title_sort SCi-XP: a Simple and Autoral Tool for Joining Artificial Intelligence to Non-Familiar People; Metrics and Visualization Performance for Unidimensional Time Series.
author Mota de Lacerda Padilha Schettini, Gabriela
author_facet Mota de Lacerda Padilha Schettini, Gabriela
Salgado Gomes de Mattos Neto, Paulo
author_role author
author2 Salgado Gomes de Mattos Neto, Paulo
author2_role author
dc.contributor.author.fl_str_mv Mota de Lacerda Padilha Schettini, Gabriela
Salgado Gomes de Mattos Neto, Paulo
description In this fast development world it is common to hear in academic environments about new tools for extracting information out of data. Unfortunately these tools that exists are made for people with previous knowledge of computer programming or coding, and in some way it excludes a little science from the practical field. Given the amount of technical tools for information mining this paper proposes a tool as an attempt of trying to join this both worlds that sometimes seems to be so distant  to a single website for prototyping time series forecasting models, to people with little to no knowledge of programming, in instants.
publishDate 2020
dc.date.none.fl_str_mv 2020-04-30
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Avaliado pelos pares
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://revistas.poli.br/index.php/repa/article/view/1339
10.25286/repa.v5i2.1339
url http://revistas.poli.br/index.php/repa/article/view/1339
identifier_str_mv 10.25286/repa.v5i2.1339
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv http://revistas.poli.br/index.php/repa/article/view/1339/611
http://revistas.poli.br/index.php/repa/article/view/1339/612
dc.rights.driver.fl_str_mv Copyright (c) 2020 Gabriela Mota de Lacerda Padilha Schettini, Paulo Salgado Gomes de Mattos Neto
http://creativecommons.org/licenses/by-nc/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Gabriela Mota de Lacerda Padilha Schettini, Paulo Salgado Gomes de Mattos Neto
http://creativecommons.org/licenses/by-nc/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
text/html
dc.publisher.none.fl_str_mv Escola Politécnica de Pernambuco
publisher.none.fl_str_mv Escola Politécnica de Pernambuco
dc.source.none.fl_str_mv Journal of Engineering and Applied Research; Vol 5 No 2 (2020): Edição Especial em Inteligência Artificial; 36-43
Revista de Engenharia e Pesquisa Aplicada; v. 5 n. 2 (2020): Edição Especial em Inteligência Artificial; 36-43
2525-4251
10.25286/repa.v5i2
reponame:Revista de Engenharia e Pesquisa Aplicada
instname:Universidade Federal de Pernambuco (UFPE)
instacron:UFPE
instname_str Universidade Federal de Pernambuco (UFPE)
instacron_str UFPE
institution UFPE
reponame_str Revista de Engenharia e Pesquisa Aplicada
collection Revista de Engenharia e Pesquisa Aplicada
repository.name.fl_str_mv Revista de Engenharia e Pesquisa Aplicada - Universidade Federal de Pernambuco (UFPE)
repository.mail.fl_str_mv ||repa@poli.br
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