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Article Dans Une Revue Annals of Work Exposures and Health Année : 2022

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

Nenad Savic
  • Fonction : Auteur
Nicolas Bovio
  • Fonction : Auteur
José Paz
  • Fonction : Auteur
Irina Guseva Canu
  • Fonction : Auteur

Résumé

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.

Dates et versions

hal-03345693 , version 1 (15-09-2021)

Identifiants

Citer

Nenad Savic, Nicolas Bovio, Fabien Gilbert, José Paz, Irina Guseva Canu. Procode: A Machine-Learning Tool to Support (Re-)coding of Free-Texts of Occupations and Industries. Annals of Work Exposures and Health, 2022, 66 (1), pp.113-118. ⟨10.1093/annweh/wxab037⟩. ⟨hal-03345693⟩
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