@inproceedings{a9ebc522e9a444caa57773ebdb12fe42,
title = "The Construction of Case Event Logic Graph for Judgment Documents",
abstract = "The construction of a case event logic graph for the judgment document can more intuitively retrospect the development of the case. This paper proposes a joint model of event extraction and relationship recognition for judgment documents. By extracting the case information in the judgment document, a case event logic graph was constructed. The development process of the case was shown, and a reference was provided for the analysis of the context of the case. The experimental results show that the proposed method can extract events and identify the relationship between events, and the F1 value reaches 0.809. The case event logic graph reveals the development context of the case accurately and vividly.",
keywords = "Event extraction, Event logic graph, Judgment document, Relationship recognition",
author = "Congyao Zhang and Shiping Tang",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Singapore Pte Ltd.; 7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021 ; Conference date: 17-09-2021 Through 20-09-2021",
year = "2021",
doi = "10.1007/978-981-16-5940-9\_16",
language = "English",
isbn = "9789811659393",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "209--217",
editor = "Jianchao Zeng and Pinle Qin and Weipeng Jing and Xianhua Song and Zeguang Lu",
booktitle = "Data Science - 7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021, Proceedings",
address = "Germany",
}