Multi-Task Deep Learning Model with an Attention Mechanism for Ship Accident Sentence Prediction
The number of ship accidents occurring in the Korean ocean has been steadily increasing year by year. The Korea Maritime Safety Tribunal (KMST) has published verdicts to ensure that the relevant personnel can share judgment on these accidents. As of 2020, there have been 3156 ship accidents; thus, i...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/12/1/233 |
| _version_ | 1797499619100327936 |
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| author | Ho-Min Park Jae-Hoon Kim |
| author_facet | Ho-Min Park Jae-Hoon Kim |
| author_sort | Ho-Min Park |
| collection | DOAJ |
| description | The number of ship accidents occurring in the Korean ocean has been steadily increasing year by year. The Korea Maritime Safety Tribunal (KMST) has published verdicts to ensure that the relevant personnel can share judgment on these accidents. As of 2020, there have been 3156 ship accidents; thus, it is difficult for the relevant personnel to study these various accidents by only reading the verdicts. Therefore, in this study, we propose a multi-task deep learning model with an attention mechanism for predicting the sentencing of ship accidents. The tasks are accident types, applied articles, and the sentencing of ship accidents. The proposed model was tested under verdicts published by the KMST between 2010 and 2019. Through experiments, we show that the proposed model can improve the performance of sentence prediction and can assist the relevant personnel to study these accidents. |
| first_indexed | 2024-03-10T03:50:00Z |
| format | Article |
| id | doaj.art-238bbd6e86e14d56ba4d472edc3960f3 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T03:50:00Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-238bbd6e86e14d56ba4d472edc3960f32023-11-23T11:09:49ZengMDPI AGApplied Sciences2076-34172021-12-0112123310.3390/app12010233Multi-Task Deep Learning Model with an Attention Mechanism for Ship Accident Sentence PredictionHo-Min Park0Jae-Hoon Kim1Department of Computer Engineering and Interdisciplinary Major of Maritime AI Convergence, Korea Maritime & Ocean University, Busan 49112, KoreaDepartment of Control & Automation Engineering and Interdisciplinary Major of Maritime AI Convergence, Korea Maritime & Ocean University, Busan 49112, KoreaThe number of ship accidents occurring in the Korean ocean has been steadily increasing year by year. The Korea Maritime Safety Tribunal (KMST) has published verdicts to ensure that the relevant personnel can share judgment on these accidents. As of 2020, there have been 3156 ship accidents; thus, it is difficult for the relevant personnel to study these various accidents by only reading the verdicts. Therefore, in this study, we propose a multi-task deep learning model with an attention mechanism for predicting the sentencing of ship accidents. The tasks are accident types, applied articles, and the sentencing of ship accidents. The proposed model was tested under verdicts published by the KMST between 2010 and 2019. Through experiments, we show that the proposed model can improve the performance of sentence prediction and can assist the relevant personnel to study these accidents.https://www.mdpi.com/2076-3417/12/1/233sentence predictionattention mechanismmulti-task learningship accident |
| spellingShingle | Ho-Min Park Jae-Hoon Kim Multi-Task Deep Learning Model with an Attention Mechanism for Ship Accident Sentence Prediction Applied Sciences sentence prediction attention mechanism multi-task learning ship accident |
| title | Multi-Task Deep Learning Model with an Attention Mechanism for Ship Accident Sentence Prediction |
| title_full | Multi-Task Deep Learning Model with an Attention Mechanism for Ship Accident Sentence Prediction |
| title_fullStr | Multi-Task Deep Learning Model with an Attention Mechanism for Ship Accident Sentence Prediction |
| title_full_unstemmed | Multi-Task Deep Learning Model with an Attention Mechanism for Ship Accident Sentence Prediction |
| title_short | Multi-Task Deep Learning Model with an Attention Mechanism for Ship Accident Sentence Prediction |
| title_sort | multi task deep learning model with an attention mechanism for ship accident sentence prediction |
| topic | sentence prediction attention mechanism multi-task learning ship accident |
| url | https://www.mdpi.com/2076-3417/12/1/233 |
| work_keys_str_mv | AT hominpark multitaskdeeplearningmodelwithanattentionmechanismforshipaccidentsentenceprediction AT jaehoonkim multitaskdeeplearningmodelwithanattentionmechanismforshipaccidentsentenceprediction |