Abstract
One of the biggest problems faced by companies is the sudden departure of employees from the company. Such events may even result in a serious paralysis of the functioning of enterprises in the event of resignation from work by people holding significant positions. Therefore, an extremely important issue is to develop techniques that will allow detecting the planned resignation of a given employee well in advance. Gaining knowledge about the factors influencing this type of events may allow for taking actions aimed at counteracting them. This work proposes a proprietary method based on the use of artificial neural networks to predict employees leaving work and to indicate which of the possible analyzed reasons are the most significant. Ultimately, the proposed system achieved an efficiency of 74 %.
The work was supported by The National Centre for Research and Development (NCBR), the project no POIR.01.01.01-00-1288/19; 2020-22.
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Korytkowski, M. et al. (2023). Employee Turnover Prediction From Email Communication Analysis. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2022. Lecture Notes in Computer Science(), vol 13589. Springer, Cham. https://doi.org/10.1007/978-3-031-23480-4_21
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