计算机科学
人工智能
智能代理
多智能体系统
知识管理
作者
Charithma Jayasekara,Inukshi Senarathne,Anjana Wickramasinghe,Nethmini Jayathilaka,Samantha Thelijjagoda,Hansi De Silva,G.G.D. Nishantha,Nilanga Abeysinghe
标识
DOI:10.1109/icac60630.2023.10417197
摘要
This system presents an innovative approach to streamline traditional recruitment processes and assist human resources in selecting the ideal candidates who align with the company's objectives. By addressing individual job requirements, the system ensures a good match between candidates' personal traits and company goals, creating a favorable environment for interviews. The Smart Recruiting System consists of four stages: Resume Parsing and NER(Named Entity Recognition) Tagging, Skill Set Classification using Big Data Analysis, Communication with New Recruiters through a Chatbot, and Improving Productivity with a Human Resource Management Portal and Skill Matrix. The process involves using advanced NLP models to extract information from resumes, including Named Entity Recognition and custom entity recognition. Big Data Analysis is used to predict job-specific skill sets and identify appropriate candidates. An automated interview system is created, analyzing candidates' behavior based on the Big 5 model. The system utilizes ASR, NLP, and deep-learning models to improve objectivity and efficiency. The Human Resource Management Portal integrates behavior analysis and candidate selection data, evaluating performance, training, and learning activities. The system identifies gaps in skills and connections, promoting cross-training and targeted development. This innovative approach combines advanced NLP, AI, and Big Data analytics to revolutionize recruitment practices. The demonstrated accuracy, efficiency, and objectivity show great potential for improving candidate selection, aligning individual skills with organizational goals, and ultimately enhancing the recruitment process.
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