دورية أكاديمية

But which skills?: Natural Language Processing tools and the identification of high-demand skills in online job advertisements

التفاصيل البيبلوغرافية
العنوان: But which skills?: Natural Language Processing tools and the identification of high-demand skills in online job advertisements
المؤلفون: Gianni Anelli
المصدر: Work Organisation, Labour and Globalisation, Vol 17, Iss 2, Pp 91-104 (2023)
بيانات النشر: Pluto Journals, 2023.
سنة النشر: 2023
المجموعة: LCC:Labor. Work. Working class
مصطلحات موضوعية: Labor. Work. Working class, HD4801-8943
الوصف: Skills assessment is essential for today’s labour market. There are many factors that change the requirements for the workplace. More than ever, it is important to monitor which skills are in high demand so that workers stay employed and companies do not lose productivity. This research discusses the relevance of data from online job portals for this task. It then uses a skill extractor in online job advertisements from Chile to identify and extract the skills employers place in their online job advertisements through skills dictionaries. The study shows modest results when using the European Skills, Competences and Occupations (ESCO) dictionary but an enhanced and much-improved result when adding an inductively constructed dictionary of the national labour market. Using this method would allow a new input of information to be incorporated into labour market information systems that would enable better decisions to be made by the various actors in the labour market.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1745-6428
1745-641X
العلاقة: https://www.scienceopen.com/hosted-document?doi=10.13169/workorgalaboglob.17.2.0091Test; https://doaj.org/toc/1745-641XTest; https://doaj.org/toc/1745-6428Test
DOI: 10.13169/workorgalaboglob.17.2.0091
الوصول الحر: https://doaj.org/article/52be09da3e8f44788234022d912248d2Test
رقم الانضمام: edsdoj.52be09da3e8f44788234022d912248d2
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:17456428
1745641X
DOI:10.13169/workorgalaboglob.17.2.0091