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Knowledge-based Hiring Recommender Model for Occasional Services in the Public Sector

Abstract:

Public employees often provide their services under contract for occasional services. This form of employment relationship may undergo the consequences of job instability. Classifying occasional job profiles allows us recommending new jobs for those who suffer from job instability. This research proposes a solution to the posed problem by using a Neutrosophic method to determine job profiles of people for the occasional service contract recommendation in the public sector. Ordered Weighted Averaging Distance (OWAD) operator is proposed for aggregation of similarities measures.