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Iterative Approach for Information Extraction and Ontology Learning from Textual Aviation Safety Reports

  • Lama SaeedaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10250)

Abstract

Textual aviation safety reports are one of the main resources that contain valuable information to understand incidents and accidents in a high-risk industry such as the aviation domain. The reporting process, hence, is essential to provide these reports. Most of the time, the reporting process is done manually, and typically, poorly structured data are provided by the reporters. Automated content analysis for these reports has attracted researchers to extract the required information to perform many tasks, and they used several techniques to achieve it. Ontologies provide formal and explicit specifications of conceptualizations and play a crucial role in the information extraction process. In this paper, we propose a novel iterative ontology-based approach of information extraction and semantic annotations for aviation safety reports and augmenting back the aviation safety ontology with new concepts and relations depending on the terms already annotated in the discovered report model.

Keywords

Information extraction Domain ontology Ontology learning Safety reports 

Notes

Acknowledgments

I want to thank Dr. Petr Křemen for his support in accomplishing this proposal. Furthermore, this work was partially supported by grants No. TA04030465 Research and development of progressive methods for measuring aviation organization’s safety performance of the Technology Agency of the Czech Republic, No. SGS16/229/OHK3/3T/13 Supporting ontological data quality in information systems of the Czech Technical University in Prague.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Faculty of Electrical EngineeringCzech Technical University in PraguePragueCzech Republic

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