Information extraction from helicopter maintenance records as a springboard for the future of maintenance text analysis

Authors:
Amber McKenzie;Manton Matthews;Nicholas Goodman;Abdel Bayoumi
Affiliations:
Department of Computer Science, University of South Carolina, Columbia, South Carolina and Condition-Based Maintenance Center, University of South Carolina, Columbia, South Carolina;Department of Computer Science, University of South Carolina, Columbia, South Carolina;Department of Mechanical Engineering, University of South Carolina, Columbia, South Carolina and Condition-Based Maintenance Center, University of South Carolina, Columbia, South Carolina;Department of Mechanical Engineering, University of South Carolina, Columbia, South Carolina and Condition-Based Maintenance Center, University of South Carolina, Columbia, South Carolina
Venue:
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
Year:
2010

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Abstract

This paper introduces a novel application of information extraction techniques to extract data from helicopter maintenance records to populate a database. The goals of the research are to preprocess the text-based data for further use in data mining efforts and to develop a system to provide a rough analysis of generic maintenance records to facilitate in the development of training corpora for use in machine-learning for more refined information extraction system design. The Natural Language Toolkit was used to implement partial parsing of text by way of hierarchical chunking of the text. The system was targeted towards inspection descriptions and succeeded in extracting the inspection code, description of the part/action, and date/time information with 80.7% recall and 89.9% precision.