Fault Knowledge Acquisition of Aircraft Based on Event Extraction Technology
Pages 566 - 571
Abstract
In order to make full use of aircraft fault information of total life cycle and construct a knowledge base for intelligent fault diagnosis, this paper preliminarily explored extracting fault knowledge from massive unstructured texts by using the event extraction technology. According to the business requirements of fault diagnosis, we defined the elements of fault events, including trigger words, and fault time, argument roles such fault time, fault occasion, fault unit, signal indicate. To extract above elements, three models, including fault event identification model, trigger extraction model and Argument extraction model is developed in this paper. The results show that this method is effective.
References
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Published In
November 2022
739 pages
ISBN:9781450396806
DOI:10.1145/3582935
Copyright © 2022 ACM.
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Association for Computing Machinery
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Publication History
Published: 10 April 2023
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- Research-article
- Research
- Refereed limited
Funding Sources
- National Natural Science Foundation of China
Conference
ICITEE 2022
ICITEE 2022: 5th International Conference on Information Technologies and Electrical Engineering
November 4 - 6, 2022
Changsha, China
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