Advanced Hr Management System: Optimizing Recruitment, Assessment, Retention, And Performance With Machine Learning
Volume 6 - Issue 10, October 2023 Edition
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Rishikopan. S; Sivarujan.S; Ramya.M; Sanduni Perera; Jivishan.T
AI, DA, HR, LSTM, ML, NLP, OE
This research paper explores four critical human resources (HR) components, focusing on leveraging advanced technology to enhance organizational performance, employee retention, and recruitment processes. The system include developing an effective reward system using machine learning techniques, employee retention prediction, recommended systems for candidate selection, and designing an automated online examination (OE) system. The first component delves into the impact of rewards on employee performance and outlines a methodology the second component focuses on employee retention prediction, emphasizing its significance in identifying factors contributing to turnover and implementing effective strategies. General parameters and key features are discussed, supported by research studies conducted by leading companies. The third component addresses the challenges faced by organizations in finding suitable candidates. It explores the use of recommended systems, leveraging social networks, and the scalability of databases. The fourth component focuses on designing and implementing an automated OE system customized based on the applicant's profile and job role. This system streamlines the recruitment process by evaluating applicants' competence and abilities. It involves collecting applicant information, identifying related keywords, and creating an intuitive interface for OE. Organizations can enhance performance, improve employee retention, and streamline recruitment by integrating AI, machine learning, data analysis, and natural language processing techniques. These advancements provide valuable insights and tools for organizations seeking to optimize their HR strategies and drive overall success.
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