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Template para relatório de seminário de conclusão de curso para o curso Tecnólogo em Análise e Desenvolvimento de Sistemas do câmpus Camaquã (IFSul). Configure no Menu o arquivo main.tex como arquivo principal do projeto.
This template is aimed to be used for articles written in French and submitted to the Journal of Interdisciplinary Methodologies and Issues in Science (JIMIS).
This template is aimed to be used for articles written in French and submitted to the Journal of Interdisciplinary Methodologies and Issues in Science (JIMIS).
Modelo para trabalho de conclusão do curso de Engenharia de Controle e Automação da Universidade Federal de Santa Catarina, Campus de Blumenau, Departamento de Engenharia de Controle Automação e Computação.
Este template contempla as exigências necessárias de formatação para o curso Superior de Análise e Desenvolvimento de Sistemas (TADS) do Instituto Federal de Educação, Ciência e Tecnologia de Goiás (IFG) - Campus Formosa.
Important Note: This template is no longer supported, but is provided for historical reference.
This template for Wiley article submissions was developed by Overleaf for the Overleaf-Wiley pilot which ran during 2017 and 2018. It was last updated in January 2019.
If you're planning to submit to a Wiley journal, please check the journal's author guidelines page for the latest information on how to prepare your submission.
The efficiency of a query execution plan depends on the accuracy of the selectivity estimates given to the query optimiser by the cost model. The cost model makes simplifying assumptions in order to
produce said estimates in a timely manner. These assumptions lead to selectivity estimation errors that have dramatic effects on the quality of the resulting query execution plans. A convenient assumption that is ubiquitous among current cost models is to assume that attributes are independent with each other. However, it ignores potential correlations which can have a huge negative impact on the accuracy of the cost model. In this paper we attempt to relax the attribute value independence assumption without unreasonably deteriorating the accuracy of the cost model. We propose a novel approach based on a particular type of Bayesian networks called Chow-Liu trees to approximate the distribution of attribute values inside each relation of a database. Our results on
the TPC-DS benchmark show that our method is an order of magnitude.
more precise than other approaches whilst remaining reasonably efficient
in terms of time and space.