Litcius/Paper detail

Job Title Predictor System

Faizan Inamdar, Dev Ojha, Chaitanya JakateDev Ojha, Yogesh Kisan Mali

2024International Journal of Advanced Research in Science Communication and Technology25 citationsDOIOpen Access PDF

Abstract

In this paper, we propose a job title recommendation system using a combination of Natural Language Processing (NLP) techniques and machine learning. We implement a TF-IDF Vectorizer and cosine similarity to recommend jobs based on user inputs like skills, experience, industry, and role category. The system was built using Python and integrated into a user-friendly interface using Streamlit, enabling personalized recommendations. We evaluate the accuracy of recommendations and discuss potential improvements

Topics & Concepts

PsychologyRecommender Systems and TechniquesData Mining Algorithms and ApplicationsIntelligent Tutoring Systems and Adaptive Learning