Analysing job advertisements and skill descriptions using NLP techniques (part 2: applying machine learning techniques and part 3: use of statistical models) - collaboration with CAO

• Main Author: Sivaramakrishnan, Hemang
• Other Authors: S Supraja
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Computer and Information Science; Engineering; Machine learning; NLP; Deep learning; Topic modelling; Data analytics; Data science
• Online Access: https://hdl.handle.net/10356/176383
• Institution: Nanyang Technological University

This paper presents a thorough investigation into the use of Natural Language Processing (NLP) and data analytics to analyse the job market for graduates, students, and job seekers. The study will use advanced NLP techniques and machine learning algorithms to dissect job- related data from a variety of sources, including job descriptions and advertisements, to identify key trends, skills, and qualifications required by various industries. The methodology includes rigorous data preprocessing and cleaning to ensure data integrity, followed by systematic textual analysis to extract useful insights. The primary goal of this project is to identify critical skill requirements and trends in the job market, providing job seekers and students with actionable insights for informed career decision-making. The project unfolds in distinct stages, each critical to the overarching goal of providing job seekers with the necessary tools and understanding to successfully navigate the complexities of the job market.