A PROFESSION RECOMMENDER SYSTEM BASED ON DEEP LEARNING AND MACHINE LEARNING APPROACHES

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 specialties based 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.
Keywords: Recommender System, Natural Language Processing , Deep learning, Universal Sentence Encoder, Uniform Manifold Approximation and Projection, HDDSCAN