Learning from text-based close call data

P. Hughes, M. Figueres-Esteban, C. van Gulijk

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)


Moving away from standard approaches of safety risk analysis to new approaches that incorporate big data analytics brings with it many opportunities to include new sources of data. These data sources could be the numeric data sources that are used for traditional safety analyses, but could also include text-based sources, such as accident reports, or even social media data feeds. This paper describes an automatic text mining approach to obtain information from close call events (accident “near misses”) that can be used for safety management decision-making. The results from this work have shown how automated text mining can be used to extract information that can be used to inform safety decisionmaking. Further research in this area intends to look at how the techniques that have been proven to date can be improved with the use of machine-learning techniques.

Original languageEnglish
Title of host publicationSafety and Reliability of Complex Engineered Systems - Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015
PublisherCRC Press/Balkema
Number of pages8
ISBN (Print)9781138028791
Publication statusPublished - 2015
Event25th European Safety and Reliability Conference: Safety and Reliability of Complex Engineered Systems - Zurich, Switzerland
Duration: 7 Sep 201510 Sep 2015


Conference25th European Safety and Reliability Conference
Abbreviated titleESREL 2015


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