| Autor: |
Al-Dossari, Hmood, Nughaymish, Fawaz Abu, Al-Qahtani, Ziyad, Alkahlifah, Mohammed, Alqahtani, Asma |
| Předmět: |
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| Zdroj: |
Engineering, Technology & Applied Science Research; Dec2020, Vol. 10 Issue 6, p6589-6596, 8p |
| Abstrakt: |
Enterprises rely more and more on well-qualified and highly specialized IT professionals. Although the increasing availability of IT jobs is a good indicator for IT graduates, they nonetheless may find themselves confused about the most appropriate career for their future. In this paper, a recommendation system called CareerRec is proposed, which uses machine learning algorithms to help IT graduates select a career path based on their skills. CareerRec was trained and tested using a dataset of 2255 employees in the IT sector in Saudi Arabia. We conducted a performance comparison between five machine learning algorithms to assess their accuracy for predicting the best-suited career path among 3 classes. Our experiments demonstrate that the XGBoost algorithm outperforms other models and gives the highest accuracy (70.47%). [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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