Automatic Classification of Academic and Vocational Guidance Questions using Multiclass Neural Network

International Journal of Advanced Computer Science and Applications(IJACSA), 10(10), 2019 ; The educational and professional orientation is an essential phase for each student to succeed in his life and his curriculum. In this context, it is very important to take into account the interests, occupations, skills, and the type of each student's personalities to make the right choice of training and to build a solid professional outline. This article deals with the problematic of educational and vocational orientation and we have developed a model for automatic classification of orientation quest... Mehr ...

Verfasser: Omar Zahour
El Habib Benlahmar
Ahmed Eddaoui
Oumaima Hourrane
Dokumenttyp: Text
Erscheinungsdatum: 2019
Verlag/Hrsg.: The Science and Information (SAI) Organization
Schlagwörter: Academic and vocational guidance / multiclass neural network / e-orientation / machine learning / Holland’s theory
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-26718236
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://doi.org/10.14569/IJACSA.2019.0101072

International Journal of Advanced Computer Science and Applications(IJACSA), 10(10), 2019 ; The educational and professional orientation is an essential phase for each student to succeed in his life and his curriculum. In this context, it is very important to take into account the interests, occupations, skills, and the type of each student's personalities to make the right choice of training and to build a solid professional outline. This article deals with the problematic of educational and vocational orientation and we have developed a model for automatic classification of orientation questions. “E-Orientation Data” is a machine learning method based on John L. Holland’s Theory of RIASEC typology that uses a multiclass neural network algorithm. This model allows us to classify the questions of academic and professional orientation according to their four categories, thus allows automatic generation of questions in this area. This model can serve E-Orientation practitioners and researchers for further research as the algorithm gives us good results. ; http://thesai.org/Downloads/Volume10No10/Paper_72-Automatic_Classification_of_Academic_and_Vocational_Guidance.pdf