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

Authors

  • César Eduardo Ochoa Díaz Universidad Regional Autónoma de Los Andes, Riobamba. Ecuador
  • Laura Alicia Colcha Ramos Universidad Regional Autónoma de Los Andes, Riobamba. Ecuador
  • María José Calderón Velásquez Universidad Regional Autónoma de Los Andes, Riobamba. Ecuador
  • Osmanys Pérez Peña Asociacion Economica Internacional Arcos - Bouygues Batiment Internacional, Holguín. Cuba

Keywords:

Single-valued neutrosophic sets, job stability, hiring of public services, OWAD

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.  

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Published

2020-11-04

Issue

Vol. 37 (2020): Neutrosophic Sets and Systems, {Special Issue: Impact of neutrosophy in solving the Latin American s social problems}

Section

SI#1,2024: Neutrosophical Advancements And Their Impact on Research

License

Copyright (c) 2020 Neutrosophic Sets and Systems

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

 Creative Commons Attribution (CC BY) license.

How to Cite

César Eduardo Ochoa Díaz, Laura Alicia Colcha Ramos, María José Calderón Velásquez, & Osmanys Pérez Peña. (2020). Knowledge-based Hiring Recommender Model for Occasional Services in the Public Sector. Neutrosophic Sets and Systems, 37, 176-183. http://fs.unm.edu/nss8/index.php/111/article/view/4106

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