正义的景象。可视化知识挖掘,法律数据和计算犯罪分析

N. Lettieri, Alfonso Guarino, Delfina Malandrino, R. Zaccagnino
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引用次数: 3

摘要

计算机犯罪分析这一新兴领域面临的挑战之一是从隐藏在刑事诉讼程序中的异构(法律和经验)信息中提取可操作的知识。检察官通常处理的信息系统不提供先进的信息提取功能,这些信息系统归结为包含投诉、犯罪记录或警察报告的数据库。在本文中,我们详述了信息可视化如何通过发挥三方面的作用来支持刑事调查中的知识挖掘:(a)描绘犯罪组织及其成员的结构和质量特征;(b)显示犯罪网络随时间的演变;(c)加强领域专家和计算启发式在知识构建过程中的交互作用。我们提出了三种可视化设计,以支持刑事调查中的知识挖掘,这些可视化已经用真实数据进行了测试,并由法律学者和公共检察官在计算犯罪分析项目中进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The sight of Justice. Visual knowledge mining, legal data and computational crime analysis
One of the challenges in the emerging field of computational crime analysis is that of extracting actionable knowledge from heterogeneous (both legal and empirical) information hidden into criminal proceedings. Public prosecutors generally deal with information systems that do not provide advanced information extraction functionalities and that boil down to databases containing complaints, criminal records or police reports. In this paper, we dwell on how information visualization can support knowledge mining in criminal investigations by playing a three-fold role: (a) depicting the structural and qualitative features of both criminal organizations and their members; (b) showing the evolution of criminal networks over time; (c) enhance the interaction between the domain expert and computational heuristics in the knowledge construction process. We present three visualizations designed to support knowledge mining in criminal investigations that have been tested with real data and evaluated by legal scholars and public prosecutors within a computational crime analysis project.
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