Abstract
In the era of artificial intelligence and big data, a large number of legal case texts have been accumulated in the process of law enforcement of marine rights protection. These case texts contain a lot of important information, such as the time, place, person, event, judgment body, judgment result and so on. The annotation of these semantic information is an important link in text analysis, mining and retrieval of sea-related cases. In this paper, a semantic annotation method based on collaborative training for maritime legal texts is proposed. The experimental results show that the method is correct and feasible.
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Acknowledgments
This work was supported by Innovation and Entrepreneurship Project for College Students in Hubei Province under Grant S201910500040; Philosophical and Social Sciences Research Project of Hubei Education Department under Grant 19Q054.
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Luo, J., Hu, Z., Liu, Q., Chen, S., Wang, P., Deng, N. (2020). Semantic Annotation in Maritime Legal Case Texts Based on Co-training. In: Barolli, L., Hellinckx, P., Natwichai, J. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2019. Lecture Notes in Networks and Systems, vol 96. Springer, Cham. https://doi.org/10.1007/978-3-030-33509-0_36
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DOI: https://doi.org/10.1007/978-3-030-33509-0_36
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