报纸文章中犯罪事件的本体

IF 0.4 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Applied Computing Review Pub Date : 2023-03-27 DOI:10.1145/3555776.3577862
Federica Rollo, Laura Po, Alessandro Castellucci
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引用次数: 1

摘要

采用语义技术表示犯罪事件可以帮助执法机构预防和调查犯罪。此外,在线报纸和社交网络是收集犯罪情报的宝贵来源。在本文中,我们提出了一种新的轻量级本体来建模犯罪事件,因为它们通常在在线新闻文章中描述。犯罪事件模型(CEM)可以集成有关犯罪的具体数据,即,犯罪发生的地点和时间,涉及的对象(作者、受害者和涉及的其他主体),发生的原因,以及有关信息来源的详细信息(例如,新闻文章)。从多个在线资源中提取结构化数据,并使用CEM将它们连接到知识图中,从而可以提取事件关系、识别模式和趋势以及推荐事件。CEM本体可在https://w3id.org/CEMontology上获得。
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CEM: an Ontology for Crime Events in Newspaper Articles
The adoption of semantic technologies for the representation of crime events can help law enforcement agencies (LEAs) in crime prevention and investigation. Moreover, online newspapers and social networks are valuable sources for crime intelligence gathering. In this paper, we propose a new lightweight ontology to model crime events as they are usually described in online news articles. The Crime Event Model (CEM) can integrate specific data about crimes, i.e., where and when they occurred, who is involved (author, victim, and other subjects involved), which is the reason for the occurrence, and details about the source of information (e.g., the news article). Extracting structured data from multiple online sources and interconnecting them in a Knowledge Graph using CEM allow events relationships extraction, patterns and trends identification, and event recommendation. The CEM ontology is available at https://w3id.org/CEMontology.
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来源期刊
Applied Computing Review
Applied Computing Review COMPUTER SCIENCE, INFORMATION SYSTEMS-
自引率
40.00%
发文量
8
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