Procode: A Machine-Learning Tool to Support (Re-)coding of Free-Texts of Occupations and Industries.

Details

Serval ID
serval:BIB_24E830FACC56
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Procode: A Machine-Learning Tool to Support (Re-)coding of Free-Texts of Occupations and Industries.
Journal
Annals of work exposures and health
Author(s)
Savic N., Bovio N., Gilbert F., Paz J., Guseva Canu I.
ISSN
2398-7316 (Electronic)
ISSN-L
2398-7308
Publication state
Published
Issued date
07/01/2022
Peer-reviewed
Oui
Volume
66
Number
1
Pages
113-118
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Abstract
Procode is a free of charge web-tool that allows automatic coding of occupational data (free-texts) by implementing Complement Naïve Bayes (CNB) as a machine-learning technique. The paper describes the algorithm, performance evaluation, and future goals regarding the tool's development. Almost 30 000 free-texts with manually assigned classification codes of French classification of occupations (PCS) and French classification of activities (NAF) were used to train CNB. A 5-fold cross-validation found that Procode predicts correct classification codes in 57-81 and 63-83% cases for PCS and NAF, respectively. Procode also integrates recoding between two classifications. In the first version of Procode, this operation, however, is only a simple search function of recoding links in existing crosswalks. Future focus of the project will be collection of the data to support automatic coding to other classification and to establish a more advanced method for recoding.
Keywords
Bayes Theorem, Humans, Industry, Machine Learning, Occupational Exposure, Occupations, Naïve Bayes, cross-validation, epidemiology, machine learning, occupational classifications
Pubmed
Web of science
Create date
29/06/2021 10:00
Last modification date
22/03/2022 7:34
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