International Journal of Computational Linguistics Research Dawei Zhang, Tengfei Wang, Meifan Ma 15 4 2024 https://doi.org/10.6025/ijclr/2024/15/4/146-152 https://www.dline.info/jcl/fulltext/v15n4/jclv15n4_3.pdf This research aims to explore the construction of a practical teaching platform for engineering applied talents based on the tag-based talent search algorithm. By building a practical teaching platform for engineering students and using the tag-based talent search algorithm, personalized assessment and matching of students can be achieved to enhance their practical abilities and employability. This study analyzes the requirements and design principles of the practical teaching platform, proposes a platform architecture based on the tag-based talent search algorithm, and validates it through practical case studies. The research finds that the practical teaching platform based on the tag-based talent search algorithm is of great significance for enhancing the practical skills of engineering students. This approach provides students with more internship opportunities and enhances their competitiveness in the job market. Moreover, the platform allows students to choose suitable internship projects based on their interests, enabling the best career development. Additionally, the platform serves as a high-quality talent supply channel for enterprises, promoting in-depth cooperation between academia and industry. The results of this research have practical significance for promoting innovation and improvement in cultivating applied talents in engineering.