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Layered ontology-based multi-sourced information integration for situation awareness

机译:基于分层的本体论的多源信息集成,以实现情境意识

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Data and information produced in network-centric environments are large and heterogeneous. As a solution to this challenge, ontology-based situation awareness (SA) is gaining attention because ontologies can contribute to the integration of heterogeneous data and information produced from different sources and can enhance knowledge formalization. In this study, we propose a novel method for enhancing ontology-based SA by integrating ontology and linked open data (LOD) called a multi-layered SA ontology and the relations between events in the layer. In addition, we described the characteristics and roles of each layer. Finally, we developed a framework to perform SA rapidly and accurately by acquiring and integrating information from the ontology and LOD based on the multi-layered SA ontology. We conducted three experiments to verify the effectiveness of the proposed framework. The results show that the performance of the SA of our framework is comparable to that of domain experts.
机译:以网络为中心的环境生成的数据和信息大而异。 作为对此挑战的解决方案,基于本体的情况意识(SA)正在获取注意力,因为在本体中可以有助于异构数据和来自不同来源产生的信息的集成,并且可以增强知识形式化。 在这项研究中,我们提出了一种新的方法,可以通过集成了本体和链接的开放数据(LOD)来增强基于本体的SA的方法,并将称为多层SA本体和图层中事件之间的关系。 此外,我们描述了每层的特征和角色。 最后,我们通过基于多层SA本体获取和集成了来自本体和LOD的信息,通过获取和集成了信息来快速准确地执行SA框架。 我们进行了三次实验,以验证拟议框架的有效性。 结果表明,我们框架的SA的性能与域专家的性能相当。

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