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        <title>Generating Realistic Synthetic Curricula Vitae for Machine Learning Applications under Differential Privacy</title>
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        <namePart type="given">Andrea</namePart>
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            <title>Proceedings of the Workshop on Ethical and Legal Issues in Human Language Technologies and Multilingual De-Identification of Sensitive Data In Language Resources within the 13th Language Resources and Evaluation Conference</title>
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            <namePart type="given">Ingo</namePart>
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    <abstract>Applications involving machine learning in Human Resources (HR, the management of human talent in order to accomplish organizational goals) must respect the privacy of the individuals whose data is being used. This is a difficult aim, given the extremely personal nature of text data handled by HR departments, such as Curricula Vitae (CVs).</abstract>
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%0 Conference Proceedings
%T Generating Realistic Synthetic Curricula Vitae for Machine Learning Applications under Differential Privacy
%A Bruera, Andrea
%A Alda, Francesco
%A Di Cerbo, Francesco
%Y Siegert, Ingo
%Y Rigault, Mickael
%Y Arranz, Victoria
%S Proceedings of the Workshop on Ethical and Legal Issues in Human Language Technologies and Multilingual De-Identification of Sensitive Data In Language Resources within the 13th Language Resources and Evaluation Conference
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F bruera-etal-2022-generating
%X Applications involving machine learning in Human Resources (HR, the management of human talent in order to accomplish organizational goals) must respect the privacy of the individuals whose data is being used. This is a difficult aim, given the extremely personal nature of text data handled by HR departments, such as Curricula Vitae (CVs).
%U https://aclanthology.org/2022.legal-1.11
%P 53-63

Markdown (Informal)

[Generating Realistic Synthetic Curricula Vitae for Machine Learning Applications under Differential Privacy](https://aclanthology.org/2022.legal-1.11) (Bruera et al., LEGAL 2022)

• Generating Realistic Synthetic Curricula Vitae for Machine Learning Applications under Differential Privacy (Bruera et al., LEGAL 2022)

ACL

• Andrea Bruera, Francesco Alda, and Francesco Di Cerbo. 2022. Generating Realistic Synthetic Curricula Vitae for Machine Learning Applications under Differential Privacy. In Proceedings of the Workshop on Ethical and Legal Issues in Human Language Technologies and Multilingual De-Identification of Sensitive Data In Language Resources within the 13th Language Resources and Evaluation Conference, pages 53–63, Marseille, France. European Language Resources Association.