Abstract
Aviation encompasses a wide range of mechanical flights as well as the aircraft business. The industry is quickly expanding as travelers choose to travel by air due to the concept of a world without borders, lower rates, and global business activities. Thus, aircraft maintenance and repair are critical jobs in the aviation sector for improved aircraft service and safety. Despite this, numerous aviation disasters occur due to a variety of factors such as malfunctioning equipment, hazardous weather conditions such as turbulence, and human error. In this research, we used text mining to explore a set of internet articles and reports about aviation occurrences and difficulties. The method retrieves frequent and significant terms from the document set. The experiment is divided into four (4) modules: (i) collecting of web articles and reports, (ii) document preprocessing, (iii) text analytics, and (iv) visualization. The experiment’s results show that the bulk of records describe aircraft maintenance, skill mismatch, and training shortages.
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Thulasy, T.N., Nohuddin, P.N.E., Rahim, N.A., Amrin, A. (2021). Literature Survey on Aircraft Maintenance Issues with Human Errors and Skill Set Mismatch Using Document Mining Technique. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2021. Lecture Notes in Computer Science(), vol 13051. Springer, Cham. https://doi.org/10.1007/978-3-030-90235-3_5
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DOI: https://doi.org/10.1007/978-3-030-90235-3_5
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