Risk Warning for Special work Based on an Event Knowledge Graph

Author(s):  
Wang Yunlong ◽  
Wang Tingchun ◽  
Mu Bo ◽  
Guo Xiaoyan ◽  
Zhang Guozhi ◽  
...  
Author(s):  
Tingting Tang ◽  
Wei Liu ◽  
Weimin Li ◽  
Jinliang Wu ◽  
Haiyang Ren

Author(s):  
Charlotte Rudnik ◽  
Thibault Ehrhart ◽  
Olivier Ferret ◽  
Denis Teyssou ◽  
Raphael Troncy ◽  
...  

2021 ◽  
Vol 2078 (1) ◽  
pp. 012024
Author(s):  
Zhen Jia ◽  
Yang Chu ◽  
Zhi Liu

Abstract This paper proposes a new tactical decision aids method based on event knowledge graph (EventKG). In the warfare domain, EventKG can be constructed through event types design, event network construction and transition probability computation between events. Initially, four event classes are introduced in accordance with the OODA loop, and eighteen subclasses are further decomposed. With the aids of a common event template, all the events taking place in the battle field can be described. Event networks are built by adopting the hierarchical task network (HTN) and described through Bayesian network, to exhibit various relations between battle events. Transition probability, namely the occurrence probability of next possible event, is computed by using the prior probability and conditional probability of event occurring. On the basis of structured EventKG, entity knowledge graph (EKG) and entity relation knowledge graph (ERKG), tactical decision aid instructions can be generated by combining with the battlefield situation information.


2009 ◽  
Author(s):  
Susanne Raisig ◽  
Herbert Hagendorf ◽  
Elke E. van der Meer
Keyword(s):  

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