Computer Engineering and Applications ›› 2023, Vol. 59 ›› Issue (23): 86-94.DOI: 10.3778/j.issn.1002-8331.2208-0294

• Pattern Recognition and Artificial Intelligence • Previous Articles     Next Articles

Research on Visualization Method of Content and Behavior Sequence for Drug-Related Cases

SHAN Zhihua, HUANG Ruizhang, DUAN Xihui, CHEN Yanping, QIN Yongbin   

  1. 1.State Key Laboratory of Public Big Data, Guizhou University, Guiyang 550025, China
    2.College of Computer Science and Technology, Guizhou University, Guiyang 550025, China
  • Online:2023-12-01 Published:2023-12-01

面向涉毒案件案情及行为序列可视化方法研究

单志华,黄瑞章,段锡辉,陈艳平,秦永彬   

  1. 1.贵州大学 公共大数据国家重点实验室,贵阳 550025
    2.贵州大学 计算机科学与技术学院,贵阳 550025

Abstract: The purpose of case visualization of drug-related cases is to show the development process of the case from different levels of detail through visualization technology and quickly understand the case. The traditional text visualization methods mostly extract text features for visualization, which will lose a large amount of important semantic information in the text and is not suitable for the visualization of drug-related cases. The visualization of the behavior sequence of drug-related cases is to display the laws of the criminal behavior through the pattern mining and sequence visualization of the behavior sequence. It makes up for the defect that it takes a lot of time and experience to manually discover the behavior rules of criminals from cases. In view of the above problems, a case text and behavior sequence visualization method is proposed. For a single case text, the method takes “sequential relationship, primary and secondary relationship” as the core idea, and constructs a case description diagram; for multiple case texts, this method extracts the behavior of the criminal in the case to construct a sequence, constructs a similar node tree to reduce the difference between the sequences, and mines and visualizes the sequence patterns. The method is applied to the data set of drug-related judicial cases provided by the Higher People’s Court of Guizhou Province, and the results of user interviews show that the method is effective. It provides practical ideas and methods for judicial and public security personnel to intuitively understand the contents of cases and explore the behavior patterns of criminals.

Key words: case visualization, judicial cases, sequence visualization, sequential pattern mining

摘要: 涉毒案件案情可视化目的是通过可视化技术从不同详细程度展现案情发展过程,快速了解案情。而传统文本可视化方法大都是提取文本特征进行可视化,这将丢失文本中大量重要语义信息,并不适合于涉毒案件案情可视化。涉毒案件行为序列可视化是通过行为序列模式挖掘和序列可视化展示犯罪人员行为中存在的规律。弥补人工从案件中发现犯罪人员行为规律需要大量时间和经验积累的缺陷。针对以上的问题,提出一种案件案情文本及行为序列可视化方法。对于单个案情文本,该方法以“先后关系、主次关系”为核心思想,构建案情描述图;对于多个案情文本,该方法抽取案情中犯罪人员的行为构建序列,构建相似节点树来降低序列之间的差异性,对序列模式挖掘并可视化。该方法在贵州省高级人民法院提供的涉毒类司法案件数据集上应用,根据用户访谈结果表明该方法是有效的,为司法和公安人员直观了解案件案情内容和探究犯罪人员存在的行为模式,提供了切实可行的思路和方法。

关键词: 案情可视化, 涉毒案件, 序列可视化, 序列模式挖掘