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 solutionsAbstract
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.
