监测近似分类知识的时变关系

T. Martin, Yun Shen
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引用次数: 6

摘要

最近有关国防信息系统的倡议强调需要汇集来自多种来源的信息,并将其融合成适合决策者的形式。本文概述了一个四阶段系统,通过提取实体和关系、识别重复实体、组织成最合适的层次类别和确定模糊类别之间的关系来融合非结构化和半结构化文本和数字数据。本文的新贡献是在过程的最后阶段,在那里我们确定模糊类别之间的关联,并确定强和/或不寻常的关联水平以及随时间的变化。演示应用程序展示了如何集成和监视来自多个来源的关于恐怖事件的信息。
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mTRACK - Monitoring time-varying relations in approximately categorised knowledge
Recent initiatives in defence related information systems have emphasised the need to bring together information from multiple sources and fuse it into a form suitable for decision makers. This paper outlines a four stage system for fusing unstructured and semi-structured text and numerical data by extraction of entities and relations, identification of duplicate entities, organisation into the most appropriate hierarchical categories and determination of relations between fuzzy categories. The novel contribution of this paper is in the final stage of the process, where we determine associations between fuzzy categories and identify strong and/or unusual levels of association as well as changes over time. A demonstrator application shows how information on terrorist incidents from multiple sources can be integrated and monitored.
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