Modeling the judgments of civil cases of support for the elderly at the district courts in Taiwan

Chao-Lin Liu, Po-Hsien Wu, Wei-Zhi Liu, Wei-Jie Li, Sieh-chuen Huang, Ho-Chien Huang

Abstract:

The problem of legal judgment prediction (LJP) has attracted substantial
attention from researchers of both the law and computer science communities
in recent years. The majority of the previous LJP work is for criminal cases. We
report our attempt to predict the judgments for the cases about the support for
the elderly, which is an instance of the civil cases. We investigated the effects
of choosing different design parameters in our decision models, which adopted
traditional machine learning and deep learning concepts. The results of the empirical
evaluations showed some encouraging results, but some others uncovered the
challenges that remain to be tackled.