Application adapted methodology of data mining in public sector information

  • Johnny Alexander Salazar Cardona
  • Marcelo López Trujillo
Keywords: Data mining, descriptive algorithms, open government, open data, predictive algorithms.

Abstract

This paper describes the results obtained in the application of process knowledge discovery and data mining in public sector information, focused on the description of the monetary and employment status of citizens in Colombia, using the methodology established in a previous research project masterly thesis of the authors of this article. This methodology is set to the topic of open data that are released in a state of open government, with the aim of discover the hidden knowledge in a set of data that will be published and shared with citizens in general, applying predictive and descriptive algorithms of data mining. With the application of this methodology we obtained trends in the data from the state, city, academic level of the person and its gender, defining specific rules for each attributes related to filter attributes, in addition it was found that the established methodology is a key guide to the success of the project, it is covers all the necessary environment for the treatment of the data and the discovery of knowledge immersed in them, but according to its characteristics can generate bottlenecks when the volume of datasets to analyze is very high.

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Published
2016-12-31
How to Cite
Salazar Cardona, J. A., & López Trujillo, M. (2016). Application adapted methodology of data mining in public sector information. UGCiencia, 22(1), 199-212. https://doi.org/10.18634/ugcj.22v.1i.701
Section
Artículos Resultado de Investigación