This paper is in the following e-collection/theme issue:

Machine Learning (1501) Occupational Health and Ergonomics/Prevention at the Workplace (241)

Published on in Vol 7, No 3 (2019): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14763, first published .
Mining Hidden Knowledge About Illegal Compensation for Occupational Injury: Topic Model Approach

Mining Hidden Knowledge About Illegal Compensation for Occupational Injury: Topic Model Approach

Mining Hidden Knowledge About Illegal Compensation for Occupational Injury: Topic Model Approach

Authors of this article:

Jin-Young Min1 Author Orcid Image ;   Sung-Hee Song2 Author Orcid Image ;   HyeJin Kim2 Author Orcid Image ;   Kyoung-Bok Min2 Author Orcid Image
Article Authors Cited by (4) Tweetations (3) Metrics

Journals

  1. Min K, Song S, Min J. Topic Modeling of Social Networking Service Data on Occupational Accidents in Korea: Latent Dirichlet Allocation Analysis. Journal of Medical Internet Research 2020;22(8):e19222 View
  2. Chan V, Ross G, Clouthier A, Fischer S, Graham R. The role of machine learning in the primary prevention of work-related musculoskeletal disorders: A scoping review. Applied Ergonomics 2022;98:103574 View
  3. Li Y, Li C, Zhang T, Wu L, Lin X, Li Y, Wang L, Yang H, Lu D, Miao D, Fang P. Questionnaires based on natural language processing elicit immersive ruminative thinking in ruminators: Evidence from behavioral responses and EEG data. Frontiers in Neuroscience 2023;17 View
  4. Park J, Park J, Jung Y, Na M, Kim Y. Characteristics of Work-related Fatal Injuries Among Aged Workers in Republic of Korea. Safety and Health at Work 2024;15(2):158 View