LEVERAGING SVM, DECISION TREES, AND BLOCKCHAIN TECHNOLOGIES FOR COMPREHENSIVE AUTOMATED RESUME SCREENING IN HUMAN RESOURCE SYSTEMS
Keywords:
SVM, decision trees, blockchain, resume screening, recruiting, HR systems, data security, automation, candidate evaluation, machine learningAbstract
Abstract: Support Vector Machines (SVM), decision trees, and blockchain technologies transform resume screening by rectifying inefficiencies in conventional recruitment methods. These technologies improve categorisation precision, interpretability, and data security, facilitating automated, transparent, and efficient candidate selection in human resource systems. Objectives: Enhance candidate assessment, bolster data security, mitigate recruiting biases, and refine resume screening through the integration of machine learning algorithms and blockchain technology. Methods: Integrates SVM for high-dimensional classification, decision trees for interpretability, and blockchain for secure credential verification, resulting in a robust data management, surpassing conventional methods. Conclusion: The integration of SVM, decision trees, and blockchain facilitates rapid, safe, and transparent recruiting, hence improving accuracy, fairness, and organisational decision- making.
