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Procode: A Machine-Learning Tool to Support (Re-)coding of Free-Texts of Occupations and Industries
Nenad Savic1, Nicolas Bovio1, Fabien Gilbert2
1Department for Health, Work and Environment, Centre for Primary Care and Public Health (Unisanté), University of Lausanne, Route de la Corniche 2, CH-1066 Epalinges-Lausanne, Switzerland.
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.
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