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Mapping of the Perception of Theft Crimes from Analysis of Newspaper Articles Online

机译:从在线报纸文章分析中分析盗窃罪的感知

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The analysis of crimes represents a great challenge to law enforcement agencies and organizations that collect information to analyze accurately and effectively the distribution of the behavior of criminal events, considering that the sources to be used in the process of generating intelligence are diverse in content and/or structure. Tools that have contributed to the analysis of fields in which massive amounts of data are available is ʺdata miningʺ, a powerful tool that can be used effectively in the analysis of large amounts of data and in the subsequent derivation of important analytical results. This paper presents a methodology of analysis of crime facts from online newspapers, identifying the different communes where the greatest number of criminal events occur, which gives an idea of potentially more dangerous places, through the detection and geographical mapping of critical points, or the analysis of the nature of the crime through the extraction of entities. Statistics that measure the predictive capacity of the model indicate that the methodology is robust to recognize crime events within the body of the news.
机译:犯罪分析对执法机构和组织来说是一个巨大的挑战,这些机构和组织收集信息以准确,有效地分析犯罪事件的行为分布,同时考虑到情报生成过程中使用的来源内容和/或方式也多种多样或结构。有助于分析其中​​可用大量数据的字段的工具是“数据挖掘”,这是一种功能强大的工具,可以有效地用于分析大量数据以及随后得出重要的分析结果。本文介绍了一种分析在线报纸上犯罪事实的方法,确定了发生犯罪事件最多的不同社区,这通过对关键点的检测和地理制图或分析给出了一个潜在的更危险场所的想法。通过提取实体来确定犯罪的性质。衡量模型预测能力的统计数据表明,该方法对于识别新闻正文中的犯罪事件具有鲁棒性。

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