计算机科学 ›› 2019, Vol. 46 ›› Issue (9): 211-215.doi: 10.11896/j.issn.1002-137X.2019.09.031
张虎1, 王鑫1, 王冲1, 程豪1, 谭红叶1, 李茹1,2
ZHANG Hu1, WANG Xin1, WANG Chong1, CHENG Hao1, TAN Hong-ye1, LI Ru1,2
摘要: 近年来,司法领域中针对法律裁判文书的分析和基于案例事实描述的结果预测已成为计算法律学的热点研究问题。法条推荐任务是基于司法案例的事实描述预测该案例适用的法条,已成为智慧司法的一项重要研究内容。通过分析法律文书的事实描述和法条的具体司法解释,挖掘司法文书事实描述部分的特征,提出了基于多模型融合的法条推荐方法。基于“中国法研杯”司法人工智能挑战赛中的公开数据,构建了3个不同规模的实验数据集,并分别在不同数据集上进行了多组实验。实验结果表明,相比于单一的法条推荐模型,所提方法能有效地提高任务的准确率,并且能较好地解决单一案例事实描述对应多个法条的推荐问题。
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