NLP based Resume Analysis and Adaptive Skill Assessment System

The proposed work introduces an innovative recruitment approach integrating LinkedIn web scraping to compile a comprehensive dataset of job descriptions and essential skills. Utilizing a pioneering Word2Vec-driven machine learning model, it efficiently categorizes job descriptions, transforming hiri...

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Bibliographic Details
Published in2024 3rd International Conference for Innovation in Technology (INOCON) pp. 1 - 5
Main Authors Julian, Anitha, K, Haripriya
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2024
Subjects
automation
candidate-role matching
hiring efficiency
Machine learning
Machine learning algorithms
Measurement
personalization
Predictive models
Recruitment
Resumes
Social networking (online)
Technological innovation
web scraping
Word2Vec embeddings
Online AccessGet full text
DOI10.1109/INOCON60754.2024.10511967

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Summary:The proposed work introduces an innovative recruitment approach integrating LinkedIn web scraping to compile a comprehensive dataset of job descriptions and essential skills. Utilizing a pioneering Word2Vec-driven machine learning model, it efficiently categorizes job descriptions, transforming hiring practices. Job seekers benefit from a dedicated platform offering concise resume summaries and a tailored algorithm for precise role matching. Automation and personalization converge to craft custom interview questions, bridging the recruiter-job seeker gap. The goal is to enhance hiring efficiency, optimize career opportunities and talent acquisition. Performance metrics validate the model's accuracy and effectiveness in job title predictions, ensuring informed decisions for both recruiters and job seekers.
DOI:10.1109/INOCON60754.2024.10511967