Abstract
Nowadays, many studies revealed a mismatch between job’s offers and demands on job market due to several factors such as the lack of reliable data and the shortage role of public mediators. Therefore we proposed a new support system for the management of unemployment.
For this purpose, we have applied a Search Hierarchical Association Rules for Knowledge algorithm (SHARK) in order to bring light on individual determinants of unemployment duration in Tunisia. Hence, Discrete-choice models have been used to establish a accurate mechanism which describes the behaviour of long-term unemployed in Tunisia.
Thus, we developed a simulator to estimate efficiently the unemployment duration in order to enhance the process of matching by public intermediaries.
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Information technologies.
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Knowledge Discovery in Databases.
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Hegland, M. (2001). Data mining techniques. Acta Numerica 2001, 10, 313–355.
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According to The National Institute of statistics of Tunisia and to ILO recommendations.
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Lachiheb, A.B.A. (2017). Intermediation and Decision Support System for the Management of Unemployment: The Simulator of Duration. In: Jallouli, R., Zaïane, O., Bach Tobji, M., Srarfi Tabbane, R., Nijholt, A. (eds) Digital Economy. Emerging Technologies and Business Innovation. ICDEc 2017. Lecture Notes in Business Information Processing, vol 290. Springer, Cham. https://doi.org/10.1007/978-3-319-62737-3_9
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