Author(s)

Suwen Li

Corresponding Author

Suwen Li

Abstract

In the process of legal translation, it is necessary to master and master the legal system and legal culture of the relevant countries. Therefore, how to eliminate the barriers of communication between the original and the translated versions of the law due to cultural differences is a necessary prerequisite and a new challenge in the process of legal translation. Based on the cultural differences in the process of translation, this paper proposes a multi-label-based feature selection algorithm, which uses the classification interval and the number of sample classification intervals to classify the translation samples, and uses the same evaluation index and data set to compare the three mature algorithms. The experimental results show that the multi-label-based feature selection algorithm proposed in this paper is average accurate. The rate is the best, which shows that the algorithm has good classification performance.

Keywords

Legal Translation; Cultural Background Differences; Multi-Tag Based Feature Selection Algorithm