Search
 
loader loading subjects...
cover
Japanese Legal Term Correction Using Random Forests
Takahiro Yamakoshi, Takahiro Komamizu, Yasuhiro Ogawa, Katsuhiko Toyama
161 - 170
10.3233/978-1-61499-935-5-161
Frontiers in Artificial Intelligence and Applications
Volume 313: Legal Knowledge and Information Systems
Abstract

We propose a method that assists legislation officers in finding inappropriate Japanese legal terms in Japanese statutory sentences and suggests corrections. In particular, we focus on sets of similar legal terms whose usages are defined in legislation drafting rules. Our method predicts suitable legal terms in statutory sentences using Random Forest classifiers, each of which is optimized for each set of similar legal terms. Our experiment shows that our method outperformed existing modern word prediction methods using neural language models.

Download
Creative Commons License