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

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 t...

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Bibliographic Details
Published in:	2022 IEEE Latin American Conference on Computational Intelligence (LA-CCI) pp. 1 - 6
Main Authors:	Rabbani, Emilia Rahnemay Kohlman, Reboucas, Juliana De Souza, De Albuquerque Neves, Marcia M., Da Luz, Gabriel Magalhaes, Do Nascimento, Willian Vieira, Da Luz, Gustavo H. Magalhaes, Lago, Felipe Guerra, De Sousa Maia, Maria Celeste, Da Silva Barros, Maicon H. L. Ferreira, Endo, Patricia Takako, Bastos-Filho, Carmelo Jose Albanez
Format:	Conference Proceeding
Language:	English
Published:	IEEE 23-11-2022
Subjects:	clustering Clustering algorithms Computational intelligence Data analysis exploratory data analysis Graphical models Procurement Proposals technological extension Technological innovation
Online Access:	Get full text
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Summary:	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.
DOI:	10.1109/LA-CCI54402.2022.9981387