Textual CBR for incident report retrieval

Authors:
David C. Wilson;Joe Carthy;Karl Abbey;John Sheppard;Ruichao Wang;John Dunnion;Anne Drummond
Affiliations:
Computer Science Department, University College Dublin, Dublin 8, Ireland;Computer Science Department, University College Dublin, Dublin 8, Ireland;Computer Science Department, University College Dublin, Dublin 8, Ireland;Computer Science Department, University College Dublin, Dublin 8, Ireland;Computer Science Department, University College Dublin, Dublin 8, Ireland;Computer Science Department, University College Dublin, Dublin 8, Ireland;Centre for Safety and Health at Work, University College Dublin, Dublin 8, Ireland
Venue:
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartI
Year:
2003

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Abstract

Incident Management Systems can play a crucial role in helping to reduce the number of workplace accidents by providing support for incident analysis. In particular, the retrieval of relevant similar incident reports can help safety personnel to identify factors and patterns that have contributed or might potentially contribute to accidents. Incident Report Retrieval is a relatively new research topic in the field of Accident Reporting and Analysis, and we are interested in developing intelligent computational support for retrieving incident information that leverages both the featural and textual components of incident reports. This paper describes InRet-T, an Incident Report Retrieval system that incorporates approaches from textual case-based reasoning to integrate both featural and textual aspects in retrieving civil aviation incident reports. It also provides a preliminary evaluation of InRet-T that offers some insight into the use of textual CBR approaches to incident analysis.