Big Data Job Analysis
Keywords:
Big Data, Job Trend Analysis, Resume Classification, Sentiment Analysis, Recommender Systems, Machine Learning, Data Mining, Career Forecasting.Abstract
In the current era of data-driven decision-making, the job market is undergoing rapid transformation due to evolving industry demands and the emergence of new technologies. This research presents a machine learning–driven framework designed to analyze big data job market trends and assess resumes using natural language processing (NLP) and sentiment analysis. By systematically processing job postings alongside candidate resumes, the system extracts in-demand skills and recommends suitable roles through a hybrid recommendation model that integrates both collaborative and content-based filtering techniques. Leveraging real-world datasets, the proposed model enhances job–candidate matching accuracy, as measured by evaluation metrics such as precision and F1-score. In addition to matching candidates to roles, the system identifies trending technologies and regional hiring trends, providing actionable insights. This intelligent, data-centric approach supports job seekers, human resource professionals, and educators in aligning workforce skills with current market requirements.
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References
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