Multi-Label Classification of Contributing Causal Factors in Self-Reported Safety Narratives
Three methods are demonstrated for automated classification of aviation safety narratives within an existing complex taxonomy. Utilizing latent semantic analysis trained against 4497 narratives at the sentence level, primary problem and contributing factor labels were assessed. Results from a sample...
Main Author: | Saul D. Robinson |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-07-01
|
Series: | Safety |
Subjects: | |
Online Access: | http://www.mdpi.com/2313-576X/4/3/30 |
Similar Items
-
From Geoportals to Geographic Knowledge Portals
by: Manfred Mittlböck, et al.
Published: (2013-03-01) -
Combination of Bayesian and Latent Semantic Analysis with Domain Specific Knowledge
by: Shen Lu, et al.
Published: (2016-06-01) -
Investigating the relationship between the business performance management framework and the Malcolm Baldrige National Quality Award framework.
by: Hossain, Muhammad Muazzem
Published: (2009) -
Synergies of Text Mining and Multiple Attribute Decision Making: A Criteria Selection and Weighting System in a Prospective MADM Outline
by: Sarfaraz Hashemkhani Zolfani, et al.
Published: (2020-05-01) -
Visualization of Knowledge Spaces to Enable Concurrent, Embedded and Transformative Input to Knowledge Building Processes
by: Teplovs, Christopher
Published: (2010)