Finding Frequent Patterns in a Technological Education Program of Pernambuco, Brazil

Emilia Rahnemay Kohlman Rabbani,Juliana De Souza Rebouças, Márcia M. De Albuquerque Neves, Gabriel Magalhães Da Luz, Willian Vieira Do Nascimento, Gustavo H. Magalhães Da Luz, Felipe Guerra Lago, Maria Celeste De Sousa Maia,Maicon H. L. Ferreira Da Silva Barros,Patricia Takako Endo,Carmelo José Albanez Bastos-Filho

2022 IEEE Latin American Conference on Computational Intelligence (LA-CCI)(2022)

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Abstract
In this paper, we present an exploratory data analysis on data regarding technological extension projects, designed by the Secretariat of Science, Technology and Innovation of the State of Pernambuco (from Portuguese, Secretaria de Ciência, Tecnologia e Inovação do Estado de Pernambuco, SECTI) and the Pernambuco Foundation for the Support of Science and Technology (from Portuguese, Fundação de Amparo à Ciência e Tecnologia de Pernambuco, FACEPE), in the state of Pernambuco, Brazil. We collected data using forms regarding the program details and applied clustering algorithms (k-means and k-modes) to find the most frequent patterns in data to check the spatial distribution and thematic distribution along the state. Results from this study are relevant for resource managers since it gives subsidies to improve future public procurement calls to better distribute proposals across the state of Pernambuco and consequently better distribute resources and democratize the knowledge.
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Key words
exploratory data analysis,clustering,technological extension
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