LIU Junnan, LIU Haiyan, CHEN Xiaohui, GUO Xuan, GUO Wenyue, ZHU Xinming, ZHAO Qingbo, LI Jia. Terrorism Event Model by Knowledge Graph[J]. Geomatics and Information Science of Wuhan University, 2022, 47(2): 313-322. DOI: 10.13203/j.whugis20190428
Citation: LIU Junnan, LIU Haiyan, CHEN Xiaohui, GUO Xuan, GUO Wenyue, ZHU Xinming, ZHAO Qingbo, LI Jia. Terrorism Event Model by Knowledge Graph[J]. Geomatics and Information Science of Wuhan University, 2022, 47(2): 313-322. DOI: 10.13203/j.whugis20190428

Terrorism Event Model by Knowledge Graph

  •   Objectives  Terrorism has received widespread attention from all over the world, and researchers have explored construction of event model. However, there are less temporal, spatial and semantic relationships in event models currently, and the diversified expression of event pose challenges to construct an event model. Therefore, it is urgent to construct a terrorism event model combining temporal, spatial and semantic features.
      Methods  Based on the analysis of event components, we propose a three-layer terrorism event model which is proposed and designed with the advanced technology of knowledge graph.
      Results  Without expanding the concepts and relationships, the multi-source heterogeneous data is integrated to represent the conceptual hierarchy of event as well as the temporal, spatial and semantic relationships.
      Conclusions  In the prototype system, the feasibility and effectiveness of the model is confirmed with three cases: Macro overview, temporal backtracking and semantic display.
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