Detalhes bibliográficos
Ano de defesa: |
2020 |
Autor(a) principal: |
OLIVEIRA, Alexandre Ronald de Araujo
![lattes](/bdtd/themes/bdtd/images/lattes.gif?_=1676566308) |
Orientador(a): |
TEIXEIRA, Mario Antonio Meireles
![lattes](/bdtd/themes/bdtd/images/lattes.gif?_=1676566308) |
Banca de defesa: |
TEIXEIRA, Mario Antonio Meireles
,
BORCHARTT, Tiago Bonini
,
ISHII, Renato Porfirio
![lattes](/bdtd/themes/bdtd/images/lattes.gif?_=1676566308) |
Tipo de documento: |
Dissertação
|
Tipo de acesso: |
Acesso aberto |
Idioma: |
por |
Instituição de defesa: |
Universidade Federal do Maranhão
|
Programa de Pós-Graduação: |
PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIA DA COMPUTAÇÃO/CCET
|
Departamento: |
DEPARTAMENTO DE INFORMÁTICA/CCET
|
País: |
Brasil
|
Palavras-chave em Português: |
|
Palavras-chave em Inglês: |
|
Área do conhecimento CNPq: |
|
Link de acesso: |
https://tedebc.ufma.br/jspui/handle/tede/3126
|
Resumo: |
The complexity of extracting knowledge from the immense amount of data generated today, creates the need and brings the opportunity to develop automated mechanisms to accelerate the knowledge discovery process, without forgetting the accuracy of the results and the increase in the productivity of analysts. The knowledge discovery process consists of several sequential, well-defined and related phases, from data selection, pre-processing, mining and evaluation, to actual discovery. This work presents a proposal for automation of the data mining stage, based on a theoretical review, requirements gathering, architecture and applications study. As a contribution, an end-user-oriented data mining environment was developed and made available in the cloud. This was positively evaluated by expert users and also used in teaching-learning and self-study scenarios of Data Science. |