Abstract
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.
Highlights
For ship accidents that occur in the Korean ocean, the relevant personnel who are involved in the accident are judged in the first court by the regional maritime safety tribunal that is nearest to the location of the accident
We propose a multi-task learning model based on the attention mechanism that simultaneously predicts accident types, applied articles, and sentences using factual information from the verdicts published by Korea Maritime Safety Tribunal (KMST)
The effectiveness of the method was verified by comparing the accuracy of the proposed multi-task learning model based on the attention mechanism and [1]
Summary
For ship accidents that occur in the Korean ocean, the relevant personnel who are involved in the accident are judged in the first court by the regional maritime safety tribunal that is nearest to the location of the accident. (3) The most common approach employed is to train a classification model with a large amount of legal data and to label the case with the corresponding sentence to perform the sentence prediction task. We evaluate a multi-task learning model that predicts accident types, applied articles, and sentences for ship accidents in the Korean ocean. After the shared layer automatically creates features from the extracted factual information, it delivers the appropriate features for the three tasks through the attention mechanism to perform the prediction tasks.
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