Visual representation of safety narratives

被引：8
|
作者：
Robinson, S. D. [1 ]
机构：
[1] St Louis Univ, Parks Coll Engn Aviat & Technol, St Louis, MO 63103 USA
来源：
SAFETY SCIENCE | 2016年 / 88卷
关键词：
LSA; Adaptive taxonomy; Safety; Isometric mapping; Machine learning;
D O I：
10.1016/j.ssci.2016.05.005
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
A computational method for the visualization of text-based safety narratives on a two dimensional plane is shown. This multi-step approach utilizes latent semantic analysis to first infer higher-order structures and then isometric mapping to reduce the projection to two dimensions. Metadata may then be overlaid on the projection. Demonstrated is the application of this process to the human coded primary-problems identified and the phase of flight for a sample of the Aviation Safety Reporting System database. It is evident that this approach provides additional insight for the analysis of large inter-related corpora commonly found in safety programs. (C) 2016 Elsevier Ltd. All rights reserved.
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页码：123 / 128
页数：6
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