Análise dos resultados do WHOQOL-100 utilizando Data Mining
Quality of Life is a well-being state which links several different aspects of everyday life and which also may be suffer interferences from outside factors, being those at times difficult to be realized, mainly when are studied carries large groups of workers with different characteristics. The ide...
| Autor principal: | Santos, Celso Bilynkievycz dos |
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| Formato: | Dissertação |
| Idioma: | Português |
| Publicado em: |
Universidade Tecnológica Federal do Paraná
2018
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| Assuntos: | |
| Acesso em linha: |
http://repositorio.utfpr.edu.br/jspui/handle/1/3613 |
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| Resumo: |
Quality of Life is a well-being state which links several different aspects of everyday life and which also may be suffer interferences from outside factors, being those at times difficult to be realized, mainly when are studied carries large groups of workers with different characteristics. The identification of such factors, potentially implicit, might serve managers as for their decisions when it comes to improve the quality of life of their collaborators and consequently the productivity. The following study throws light over a complementary analysis using Data Mining techniques in an innovative mode. A Study of case was carried out approaching worker of college from a public institution, using the WHOQOL-100 as a data collector. In order to obtain implicit knowledge, the Procedure of Knowledge Discovery in Databases phases was taken, using it on the Data Mining, Rules of Association techniques. It is concluded that the Data Mining techniques, more specifically, the Rules of Association ones, can be used as an addition when it comes to analysis results of an instrument of study based upon surveys, mainly when a huge number of additional data is held and the implicit knowledge is the main focus to be figured. The planning as well as the use of combined measures of subjective and objective interest allowed the decrease of operational tasks costs as for the very description of the Procedure of Knowledge Discovery in Databases, Rules of Association. |
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