管理评论

管理评论 ›› 2022, Vol. 34 ›› Issue (6): 143-152.

• 电子商务与信息管理 • 上一篇    下一篇

基于文本挖掘的检察起诉决策支持与案卷分类管理系统

石勇1,2,3,4, 安文录1,5, 曲艺1,2,3   

  1. 1. 中国科学院大学经济与管理学院, 北京 100190;
    2. 中国科学院虚拟经济与数据科学研究中心, 北京 100190;
    3. 中国科学院大数据挖掘与知识管理重点实验室, 北京 100190;
    4. College of Information Science and Technology, University of Nebraska at Omaha, NE 68182, USA;
    5. 上海市浦东新区人民检察院, 上海 200135
  • 收稿日期:2020-09-29 出版日期:2022-06-28 发布日期:2022-07-22
  • 通讯作者: 曲艺(通讯作者),中国科学院大学经济与管理学院、中国科学院虚拟经济与数据科学研究中心、中国科学院大数据挖掘与知识管理重点实验室博士研究生。
  • 作者简介:石勇,中国科学院大学经济与管理学院教授,中国科学院虚拟经济与数据科学研究中心主任,中国科学院大数据挖掘与知识管理重点实验室主任,Distinguished Chair Professor,College of Information Science and Technology,University of Nebraska at Omaha,博士生导师;安文录,中国科学院大学经济与管理学院博士研究生,上海市浦东新区人民检察院副检察长。
  • 基金资助:
    国家自然科学基金重点项目（71932008）。

A Prosecution Decision Support and Cases Files Classification Management System Based on Text Mining

Shi Yong1,2,3,4, An Wenlu1,5, Qu Yi1,2,3   

  1. 1. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190;
    2. Research Center on Fictitious Economy & Data Science, Chinese Academy of Sciences, Beijing 100190;
    3. Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190;
    4. College of Information Science and Technology, University of Nebraska at Omaha, NE 68182, USA;
    5. People's Procuratorate of Shanghai Pudong New District, Shanghai 200135
  • Received:2020-09-29 Online:2022-06-28 Published:2022-07-22

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摘要： “智慧检务”建设近些年取得了巨大的进展，但是大部分集中于检察信息化和数据基础设施领域，对检务工作决策支持的关注程度和相关研究成果都很有限。针对这一弱项，围绕检察工作中“对刑事犯罪提起公诉”的核心任务，结合检察官“根据案情基本信息决定以何种罪名起诉”的决策过程，本文运用文本挖掘技术建立起一套检察起诉决策支持系统。该系统主要由文本预处理、特征提取、分类等流程组成，输入是案情描述的文本，输出是对应的起诉罪名。实验结果显示，该系统在多种分类模型下、不同的特征数量下、不同的文本向量表示方法下均能取得较高的准确率，不仅实现了有效的、高精度的起诉决策支持，也提升了案卷分类管理的效率。本文成果是大数据挖掘辅助检务决策领域的率先尝试，是提高检务工作智能化水平的具体实践，丰富了领域研究的同时，相关数据和结论亦可作为该领域应用和实践的基线，供未来参考和借鉴。

关键词: 文本挖掘, 文本分类, 起诉决策支持, 案卷分类管理

Abstract: The construction of "smart prosecution" has made great progress in recent years. However, most of the achievements are mainly in the field of prosecution informatization and data infrastructure development, with very few researches and very limited attention on decision support for prosecution. To fill this gap, based on factor that the core task in prosecution is to "prosecute criminal offenses" and prosecutors "decide which charge to prosecute according to the basic case information", this paper uses text mining techniques to establish a text classification-based decision support system for prosecution. This system mainly consists of text pre-processing, feature extraction, classification and other processes while it inputs the cases description text and automatically outputs the corresponding prosecution charges. Experimental results show that this system can achieve high accuracy with various classification models, different number of features input and different text vector representation methods. It not only achieves effective and high-precision prosecution decision support, but also improves the efficiency of case file classification management. Our research work in this paper is a pioneering attempt in the field of big data mining-assisted prosecution decision making and a concrete practice of "promoting the intelligence of prosecution". Our findings enrich the field of research and provide relevant data and conclusions that can be used as a baseline for future application and practice in this field.

Key words: text mining, text classification, decision support in prosecution, cases files classification and management