A Data-Mining Approach to Identification of Risk Factors in Avia

第十届中国R会议【合肥】

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A Data-Mining Approach to Identification of Risk Factors in Avia

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We present a data-mining approach to incident risk factor identification and analysis using incident data from the Federal Aviation Safety Board. Timely and accurate analysis of these reports is vital to the improvement of aviation safety. But extensive manual identification of risk factors by human experts and incomplete data present daunting challenges. Frist, topical mining techniques are used to convert underutilized textual data in the form of incident narratives to serve as input. Second, data streaming algorithms allow efficient training of risk factor classification models. The results show promise of such an approach not only as a potential approach to process daily influx of incident reports but also a more efficient way of building a classification model. The identification of risk factors is an important step to closing the gap between incident reporting and safety management systems.

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