NLP and Semantic Matching Algorithms with Blockchain: Advancing AI Powered Resume Classification for Enhanced Job Candidate Matching
Keywords:
Natural Language Processing, semantic alignment, blockchain technology, artificial intelligence, curriculum vitae classification, recruiting, data protection, employment matching, hiring enhancement, human resources solutions.Abstract
Natural Language Processing (NLP), semantic matching, and blockchain
technology are revolutionising resume categorisation by facilitating efficient data processing,
context-sensitive job matching, and safe credential verification, thereby overcoming the
shortcomings of conventional recruitment practices.
Objectives: Improve candidate-job compatibility, increase recruitment precision, guarantee
data protection, and optimise hiring procedures through the integration of powerful AI-driven
technology.Methods: The study integrates natural language processing for data extraction, semantic
algorithms for context-based matching, and blockchain technology for secure credential
validation to create a comprehensive recruitment system.
Empirical Results: The suggested model attains an accuracy of 96.3%, precision of 95.0%,
recall of 95.8%, and demonstrates strong data security, surpassing conventional methods
in recruitment operations.
Conclusion: The integration of NLP, semantic matching, and blockchain enhances recruitment
accuracy, guarantees secure data management, and streamlines hiring processes, facilitating
the development of novel, AI-driven HR solutions
