Design and Evaluation of a Smart Graduate Recruitment Filtering System Based on BDOBD Model: Practical Application in Vietnam

Abstract

Digital transformation in higher education and human resource development is creating many difficulties for graduate recruitment, especially in Vietnamese universities. Common problems include: data is scattered in many places, systems are not connected to each other, student records are not unified, and the checking and verification of degrees are slow and ineffective. This study proposes the publication of a Blockchain-Based Ontology-Supported Big Data (BDOBD) design study as a comprehensive information filtering system to address the stated problems. The proposed solution framework logically analyzes three core technologies: Big Data facilitates rapid high-volume application profile verification; Ontology maps application skills with tools required by employers; Blockchain provides registration, analysis, anti-fraud, information security, and prevents profile falsification. The system is built through a multi-tiered architecture and is detailed practically through simulation. Practical results show that this model has improved the accuracy of recruitment decisions. Furthermore, BDOBD reduces processing time and associated costs by approximately three parts, while ensuring transparency and reliability of data throughout the readiness filtering process.