This paper presents the application of some Computational Intelligence methods for obtaining a classifier analysing employees to form work groups. The proposed bio-inspired solution analyses employees using data gathered from their professional attitudes and skills, then suggests how to form groups of human resources within a company that can effectively work together. The same proposed tool provides employers with a fair and effective means for employee evaluation. In our approach, employee profiles are processed by a dedicated Radial Basis Probabilistic Neural Network based classifier, which finds non-explicit custom-created groups. The accuracy of the classifier is very high, revealing the potential efficacy of the proposed bio-inspired classification system.

Toward work groups classification based on probabilistic neural network approach

NAPOLI, CHRISTIAN;PAPPALARDO, Giuseppe;TRAMONTANA, EMILIANO ALESSIO;
2015-01-01

Abstract

This paper presents the application of some Computational Intelligence methods for obtaining a classifier analysing employees to form work groups. The proposed bio-inspired solution analyses employees using data gathered from their professional attitudes and skills, then suggests how to form groups of human resources within a company that can effectively work together. The same proposed tool provides employers with a fair and effective means for employee evaluation. In our approach, employee profiles are processed by a dedicated Radial Basis Probabilistic Neural Network based classifier, which finds non-explicit custom-created groups. The accuracy of the classifier is very high, revealing the potential efficacy of the proposed bio-inspired classification system.
2015
978-3-319-19323-6
Neural Networks; Collaborative Networks; Artificial Intelligence
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/72516
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