Journal
APPLIED SCIENCES-BASEL
Volume 12, Issue 23, Pages -Publisher
MDPI
DOI: 10.3390/app122311971
Keywords
dependency parsing; equipment maintenance documents; named entity recognition
Categories
Funding
- Ministry of Land, Infrastructure Transport [RS-2022-00143813]
- Ministry of Trade, Industry Energy [20009185]
- [21ATOGC161932-01]
- Korea Evaluation Institute of Industrial Technology (KEIT) [20009185] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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This paper presents a text-based research method to extract key information and knowledge from equipment maintenance documents, addressing issues related to semantically ambiguous expressions. By utilizing named entity recognition and dependency parsing methods, maintenance knowledge was effectively extracted.
In enterprises operating large-scale equipment, such as plants, maintenance workers must quickly and accurately find and understand the information in the equipment maintenance documents to perform maintenance tasks effectively. If the equipment maintenance documents include sentences with semantically ambiguous expressions, it will interfere with the maintenance knowledge search, and it may affect the maintenance performance of engineers. In order to solve these problems, text-based research of maintenance documents have been done to extract the key information or knowledge from these documents. Previous studies focused on finding the technical terminologies or calculating the similarity of documents using named entity recognition approaches. This paper proposes a method to extract knowledge of not only the technical terminologies but also their relations. The proposed method uses a rule-based approach that can be applied to the results of a named entity recognition approach and a dependency parsing approach. The named entity recognition approach found technical terms and the dependency parsing approach provided sentence structure information, so that the proposed method showed that a set of rules can extract maintenance knowledge, including entities and their relations. Trouble-shooting documents in the field were used as an experiment to demonstrate the effectiveness of the proposed method, and the experiment showed the possibility of practical use of the proposed method.
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