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:2019,28(7):206-213
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基于知识图谱的盗窃案件法律文书智能推理研究
(1.太原科技大学 计算机科学与技术学院, 太原 030024;2.中北大学 大数据学院, 太原 030024)
Research on Intelligent Reasoning of Legal Documents in Theft Case Based on Knowledge Graph
(1.School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan 030024, China;2.School of Big Data, North University of China, Taiyuan 030024, China)
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投稿时间:2019-01-09    修订日期:2019-02-03
中文摘要: 在检察官办案过程中对盗窃案件性质把握不准确,对量刑建议给出缺乏经验,导致给出的量刑建议准确性不足.为了使检察官给出更加准确的量刑建议,提供辅助量刑参考,通过对盗窃案件法律文书理论和知识体系进行整理和分析,对其中的隐式关系、深层关系进行挖掘、推理,通过搭建本体模型,提出了基于本体的盗窃案件法律文书知识图谱构建方法,并且设计自定义推理规则,实现了盗窃案件法律文书知识图谱在相似量刑类案推送测试功能,得到了理想的测试结果.研究证明,构建基于本体的盗窃案件法律文书知识图谱,利用智能推理技术,给检察官提供相似案件量刑参考,辅助了检察官给出更加合理的量刑建议.
Abstract:In the process of handling the case by the prosecutor, the nature of the theft case is not accurate, and the lack of experience in the sentencing suggestion leads to insufficient accuracy of the sentencing recommendations. In order to enable the prosecutor to give more accurate sentencing recommendations, provide an auxiliary sentencing reference, through the collation and analysis of the legal documents theory and knowledge system of the theft case, excavate and reason the implicit relationship and deep relationship, and build the ontology model. This study proposes a method for constructing knowledge graphs of legal documents based on ontology, and designs custom inference rules. It realizes the knowledge of the legal documents of theft cases in similar sentencing cases, and obtains the ideal test results. The research proves that the knowledge graph of the legal documents based on ontology-based theft cases is constructed, and the intelligent reasoning technology is used to provide the prosecutor with a similar case sentencing reference, which assists the prosecutor to give more reasonable sentencing suggestions.
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基金项目:太原科技大学校博士启动基金(20162029);山西省重点研发计划(201703D111011)
引用文本:
乔钢柱,冯婷婷,张国晨.基于知识图谱的盗窃案件法律文书智能推理研究.计算机系统应用,2019,28(7):206-213
QIAO Gang-Zhu,FENG Ting-Ting,ZHANG Guo-Chen.Research on Intelligent Reasoning of Legal Documents in Theft Case Based on Knowledge Graph.COMPUTER SYSTEMS APPLICATIONS,2019,28(7):206-213

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