Contrast-Set Mining of Aircraft Accidents and Incidents

Authors:
Zohreh Nazeri;Daniel Barbara;Kenneth Jong;George Donohue;Lance Sherry
Affiliations:
George Mason University, Fairfax, USA 22030;George Mason University, Fairfax, USA 22030;George Mason University, Fairfax, USA 22030;George Mason University, Fairfax, USA 22030;George Mason University, Fairfax, USA 22030
Venue:
ICDM '08 Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
Year:
2008

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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 datain contrast to the aircraft incident datain 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.