Artificial Intelligence Techniques in Human Resource Management

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Ai Method
Ai Strategy
AI System
Ai Technique
AI Technology
artificial intelligence for workforce management
Band Id
Category=KJMV2
Category=UYQ
Computer Engineering
enterprise resource planning
eq_bestseller
eq_business-finance-law
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Fabric Defect Detection
Fuzzy Linguistic Variables
Fuzzy Logic
Hr Professional
HRM Function
Human Resources & Training
Human Robot Collaboration
image processing techniques
industry 4.0 applications
IoT Device
Linear Programming
linear programming approach
manpower optimization
Membership Function
Ml Algorithm
Network Lifetime
OLED Display
Particle Swarm Optimization
Recruitment Process
RGB.
Sensor Nodes
Smart Band
Smart Computing
smart computing integration
Wireless Sensor Networks

Product details

  • ISBN 9781774911686
  • Weight: 780g
  • Dimensions: 156 x 234mm
  • Publication Date: 18 Aug 2023
  • Publisher: Apple Academic Press Inc.
  • Publication City/Country: CA
  • Product Form: Hardback
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This new volume presents a range of techniques that aim to enhance the operation of human resource management by applying state-of-the-art artificial intelligence technology. With illustrative case studies, the volume uses examples from several real-life problems and includes their possible solutions using advanced AI technology. The book explores the confluence of smart computing and traditional businesses to foster productivity, profitability, and prosperity and goes on to apply AI techniques in the recruitment process, with enterprise resource planning management software, for manpower optimization systems in colleges, for creating uniformity in HRM across organizations, for creating conflicting strategy management techniques, and more. One pandemicrelated chapter discusses the use of radio frequency-based technology for monitoring social distancing.

Soumi Ghosh, PhD, is Assistant Professor in the Information Technology Department of Maharaja Agrasen Institute of Technology, Delhi, India. She has published many research papers in Scopus/ SCI-indexed international journals and conferences. Her research areas include data mining, artificial intelligence, software engineering, data analysis, computational intelligence, machine learning, pattern recognition, and fuzzy logic.

Soumi Majumder is Associate Researcher at the Universidad Internacional de La Rioja, Logroño, La Rioja, Spain, and in the Business Administration Department at the Future Institute of Engineering and Management, Kolkata, India. She is associated with Sister Nivedita University, Kolkata, India, and Netaji Subhash Engineering College, Kolkata, India. She has published books and research papers on quality work-life, decent work-life, work-life balance, stress management, employee engagement, job satisfaction, leadership, and training and learning.

Santosh Kumar Das, PhD, is Assistant Professor in the Department of Computer Science and Engineering at Sarala Birla University, Ranchi, India. Prior to that, he was Assistant Professor at the School of Computer Science and Engineering at the National Institute of Science and Technology (Autonomous), Institute Park, Odisha, India. He has more than eight years of teaching experience and has authored and edited five books and published several research papers. His research interests focus on ad-hoc and sensor networks, artificial intelligence, soft computing, and mathematical modeling.