Proposal of information analysis system on latent human error

Tatsuya Shimada, Riku Tsunori, Kasumi Koike, Yusaku Okada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Latent Human Error information is gathered in companies, but there is a problem that it cannot be used well. The problem behind it is lack of knowledge on trouble analysis and insufficient analysis on text data. Therefore, in this research, we propose an information analysis system on latent human error. In the analysis system, the following three important elements are included. The first point is knowledge of Human Factors which is useful for trouble analysis. The second point is natural language processing technology which processes text information on trouble. The third point is statistics and DeepLearning technology using processed text information. Based on these factors, we aim to build an analysis support system that can be used by people who are not familiar with trouble analysis at the company site.

Original languageEnglish
Title of host publicationAdvances in Human Error, Reliability, Resilience, and Performance - Proceedings of the AHFE 2019 International Conference on Human Error, Reliability, Resilience, and Performance
EditorsRonald L. Boring
PublisherSpringer Verlag
Pages271-275
Number of pages5
ISBN (Print)9783030200367
DOIs
Publication statusPublished - 2020 Jan 1
EventAHFE International Conference on Human Error, Reliability, Resilience, and Performance, 2019 - Washington D.C., United States
Duration: 2019 Jul 242019 Jul 28

Publication series

NameAdvances in Intelligent Systems and Computing
Volume956
ISSN (Print)2194-5357

Conference

ConferenceAHFE International Conference on Human Error, Reliability, Resilience, and Performance, 2019
CountryUnited States
CityWashington D.C.
Period19/7/2419/7/28

Keywords

  • Human factors
  • Latent Human Error
  • Machine learning

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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