Using Data Mining Techniques to Discover Patterns in an Airline's Flight Hours Assignments

Francisco Javier Villar Martín, Jose Luis Castillo Sequera and Miguel Angel Navarro Huerga
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Francisco Javier Villar Martín: Department of Computer Science, University of Alcalá, Alcalá de Henares, Spain
Jose Luis Castillo Sequera: Department of Computer Science, University of Alcalá, Alcalá de Henares, Spain
Miguel Angel Navarro Huerga: Department of Computer Science, University of Alcalá, Alcalá de Henares, Spain

International Journal of Data Warehousing and Mining (IJDWM), 2017, vol. 13, issue 2, 45-62

Abstract: The quality of a company's information system is essential and also its physical data model. In this article, the authors apply data mining techniques in order to generate knowledge from the information system's data model, and also to discover and understand hidden patterns within data that regulate the planning of flight hours of pilots and copilots in an airline. With this objective, they use Weka free software which offers a set of algorithms and visualization tools geared to data analysis and predictive modeling of information systems. Firstly, they apply clustering to study the information system and analyze data model; secondly, they apply association rules to discover connection patterns in data; and finally, they generate a decision tree to classify and extract more specific patterns. The authors suggest conclusions according these information system's data to improve future decision making in an airline's flight hours assignments.

Date: 2017
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