NLP And Semantic Matching Algorithms With Blockchain: Advancing AI-Powered Resume Classification For Enhanced Job Candidate Matching

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.