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Extracting information from free-text aircraft repair notes
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IEA/AIE'2003 Proceedings of the 16th international conference on Developments in applied artificial intelligence
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Authoring cases from free-text maintenance data
MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
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This paper describes the Integrated Diagnostic System (IDS), an applied AI project concerned with the development of hybrid information systems to diagnose problems and help manage repair processes of commercial aircraft fleets. A study at one major airline indicated that significant benefits could accrue (approximately 2% of overall maintenance budget) through the use of innovative information technology. The IDS prototype (currently in extended field trial) takes as input a stream of messages representing maintenance and diagnostic events. These are filtered and aggregated in order to yield information in an appropriate form for various decision making tasks (and in particular for the maintenance staff while performing fault isolation and repair procedures). IDS was built using ART*Enterprise® and makes extensive use of its rule-based and case-based reasoning facilities in order to apply various sources of knowledge (manuals, heuristics, historical data) to this problem. As well as technical issues, this paper discusses the motivation for and methodology followed in this project.