Automatic Course of Action Generation using Soft Data for Maritime Domain Awareness

被引:3
|
作者
Plachkov, Alex [1 ]
Abielmona, Rami [2 ]
Harb, Moufid [2 ]
Falcon, Rafael [2 ]
Inkpen, Diana [1 ]
Groza, Voicu [1 ]
机构
[1] Univ Ottawa, Sch Elect Engn & Comp Sci, Ottawa, ON K1N 6N5, Canada
[2] Larus Technol Corp, Res & Engn, Ottawa, ON, Canada
关键词
course of action recommendation; decision support systems; multicriteria decision making; high-level information fusion; soft data;
D O I
10.1145/2908961.2931678
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Information Fusion (IF) systems have long exploited data provided by hard (physics-based) sensors with the aspiration of making sense of the environment they are monitoring. In recent times, the IF community has recognized the potential of utilizing data generated by people, also known as soft data. In this study, we demonstrate how course of action (CoA) generation, one of the key elements of Level 3 High Level Information Fusion and a vital component for security and defense decision support systems, can be augmented using soft (human-derived) data for improved mission effectiveness. This conceptualization is validated through an elaborate experiment situated in the maritime world. To the best of the authors' knowledge, this is the first study to apply soft data to automatic CoA generation in the maritime domain.
引用
收藏
页码:1071 / 1078
页数:8
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