Abstract
Identifying patterns of factors associated with aircraft accidents is of high interest to the aviation safety community. However, accident data is not large enough to allow a significant discovery of repeating patterns of the factors. We applied the STUCCO algorithm to analyze aircraft accident data in contrast to the aircraft incident data in major aviation safety databases and identified factors that are significantly associated with the accidents. The data pertains to accidents and incidents involving commercial flights within the United States. The NTSB accident database was analyzed against four incident databases and the results were compared. We ranked the findings by the Factor Support Ratio, a measure introduced in this work.
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© 2008 Springer-Verlag Berlin Heidelberg
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Nazeri, Z., Barbara, D., De Jong, K., Donohue, G., Sherry, L. (2008). Contrast-Set Mining of Aircraft Accidents and Incidents. In: Perner, P. (eds) Advances in Data Mining. Medical Applications, E-Commerce, Marketing, and Theoretical Aspects. ICDM 2008. Lecture Notes in Computer Science(), vol 5077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70720-2_24
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DOI: https://doi.org/10.1007/978-3-540-70720-2_24
Publisher Name: Springer, Berlin, Heidelberg
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