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Erschienen in:
Applying Semantic Web Technologies to Assess Maintenance Tasks from Operational Interruptions: A Use-Case at Airbus Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

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

verfasst von : Lama Saeeda

Erschienen in: The Semantic Web

Verlag: Springer International Publishing

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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.

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Vorheriges Kapitel A Knowledge-Based Framework for Improving Accessibility of Web Sites
Nächstes Kapitel Integrative Data Management for Reproducibility of Microscopy Experiments
Fußnoten
1
A preliminary report is created by the safety department of an organization and sent to the authority.
 
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Metadaten
Titel
Iterative Approach for Information Extraction and Ontology Learning from Textual Aviation Safety Reports
verfasst von
Lama Saeeda
Copyright-Jahr
2017
Buch
The Semantic Web

Print ISBN: 978-3-319-58450-8

Electronic ISBN: 978-3-319-58451-5

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-58451-5_18

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