Natural Language Processing System for Text Classification Corpus Based on Machine Learning
Author: 
Yawen SuAuthors Info & Claims
Yawen SuAuthors Info & ClaimsArticle No.: 123, Pages 1 - 15
Abstract
A classification system for hazardous materials in air traffic control was investigated using the Human Factors Analysis and Classification System (HFACS) framework and natural language processing to prevent hazardous situations in air traffic control. Based on the development of the HFACS standard, an air traffic control hazard classification system will be created. The dangerous data of the aviation safety management system is selected by dead bodies, classified and marked in five levels. Time Frame Return Frequency TextRank text classification method based on key content extraction and text classification model based on Convolutional Neural Network and Bidirectional Encoder Representations from Transforms models were used in the experiment to solve the problem of small samples, many labels and random samples in hazardous environment of air pollution control. The results show that the total cost of model training time and classification accuracy is the highest when the keywords are around 8. As the number of points increases, the time spent in dimensioning decreases and affects accuracy. When the number of points reaches about 93, the time spent in determining the size increases, but the accuracy of the allocation remains close to 0.7, but the increase in the value of time leads to a decrease in the total cost. It has been proven that extracting key content can solve text classification problems for small companies and contribute to further research in the development of security systems.
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Index Terms
- Natural Language Processing System for Text Classification Corpus Based on Machine Learning
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Published In
August 2024
343 pages
EISSN:2375-4702
DOI:10.1145/3613611
- Editor:
- Imed Zitouni,
- Guest Editors:
- Deepak Kumar Jain,
- Thierry Boumans,
- Stefano Berretti
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 08 August 2024
Online AM: 19 February 2024
Accepted: 31 January 2024
Revised: 24 December 2023
Received: 30 October 2023
Published in TALLIP Volume 23, Issue 8
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- Study on Application Limits and ethical Risk Assessment of rural Artificial Intelligence Education
- Fujian Province Education Science “14th Five-year Plan” 2022 annual special
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