An expert system for job matching of the unemployed

This paper presents an expert system for evaluation of the unemployed at certain offered posts. The expert application uses Neuro-Fuzzy techniques for analyzing a corporate database of unemployed and enterprises profile data. The process of matching an unemployed with an offered job is performed through a Sugeno type Neuro-Fuzzy inference system. Large training sets of old historical records of unemployed (belonging to the same social class), rejected or approved at several posts, (provided by the Greek General Secretariat of Social Training) were used to define the weights of the system parameters. New instances of rejected or approved cases arriving become part of the training set. Retraining is performed after a standard amount of new cases available. The system output is a measure of the unemployed suitability for the certain job (evaluation mark). q 2003 Elsevier Ltd. All rights reserved.