| 摘 要: 面向法律领域的相关问题,需要借助专业的法律文本。利用司法领域的文本资源解决用户提出的合同法 律问题,能在很大程度上降低人工成本,节约社会资源。为了更加智能、高效地响应用户在合同法方面的法律诉求问 题,本文设计与实现了一个合同法律智能问答系统,并给出了一种基于文本卷积神经网络(Text-CNN)的联合分类与匹 配的合同法律智能问答深度学习模式,针对合同法领域的文本特征,对其进行了分类。实验表明,该模式适合于合同法 领域的智能问答。 |
| 关键词: 合同法律智能问答系统;文本卷积神经网络;自然语言处理;词向量 |
|
中图分类号: TP391.1
文献标识码: A
|
|
| Research on Intelligent Contract Law Question-and-Answer System based on Text-CNN Joint Classi cation and Matching |
|
LIU Gehong, LI Jinze, LI Bianting, SHAO Nanqing, DOU Wanfeng
|
( Nanjing Normal University, Nanjing 210023, China)
1512509129@qq.com; 739036728@qq.com; libianting1999@163.com; 18001576758@163.com; douwanfeng@njnu.edu.cn
|
| Abstract: Relevant issues in the legal eld require professional legal texts. The text resources in the judicial eld can be used to deal with the legal questions concerning contracts raised by users, which can greatly reduce labor cost and save social resources. In order to more intelligently and ef ciently respond to users' legal claims in contract law, this paper designs and implements an intelligent contract law Question and Answer System (QAS), and proposes a deep learning model of intelligent QAS focusing on contract law based on the technology of joint classi cation and matching of Text Convolutional Neural Network (Text-CNN), which can classify different texts of contract law according to their characteristics. Experiments show that this model is suitable for intelligent question answering in the eld of contract law. |
| Keywords: intelligent contract law question-and-answer system; Text-CNN; natural language processing; word vector convolutional neural network;natural language processing;the word vector |
