A PROFESSION RECOMMENDER SYSTEM BASED ON DEEPLEARNING AND MACHINE LEARNING APPROACHES

The issue of uncertain career path choice among modern schoolchildren has become increasingly prominent, resulting in a substantial decrease in the number of university students. This uncertainty has become a major concern as students and their parents are often unfamiliar with the wide range of available professions, particularly those that have emerged in the last decade. A modern solution is proposed in the form of a web application that uses Deep Learning, Machine Learning, and NLP to recommend suitable specialtiesbased on the competencies required for the profession. The system will analyze and extract implicit features through a supervised classification approach, providing a comprehensive solution for profession search in the Kazakhstan market.

Authors

Publication Details

Journal
Suleyman Demirel University Bulletin Natural and Technical Sciences
Published
2024-10-15
DOI
https://doi.org/10.47344/sdubnts.v62i1.946
Primary Topic
Educational Technology and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A PROFESSION RECOMMENDER SYSTEM BASED ON DEEPLEARNING AND MACHINE LEARNING APPROACHES

Farukh Iskalinov
Suleyman Demirel University Bulletin Natural and Technical Sciences
Educational Technology and Pedagogy
article

A PROFESSION RECOMMENDER SYSTEM BASED ON DEEPLEARNING AND MACHINE LEARNING APPROACHES

Farukh Iskalinov
article en

Abstract

The issue of uncertain career path choice among modern schoolchildren has become increasingly prominent, resulting in a substantial decrease in the number of university students. This uncertainty has become a major concern as students and their parents are often unfamiliar with the wide range of available professions, particularly those that have emerged in the last decade. A modern solution is proposed in the form of a web application that uses Deep Learning, Machine Learning, and NLP to recommend suitable specialtiesbased on the competencies required for the profession. The system will analyze and extract implicit features through a supervised classification approach, providing a comprehensive solution for profession search in the Kazakhstan market.

Suleyman Demirel University Bulletin Natural and Technical SciencesVol. 62(1)
Openalex Percentile: Top 76%
Educational Technology and Pedagogy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.