Big Data-Supported Analysis Model for Matching Vocational School Majors with Industry Needs
Main Article Content
Abstract
The dynamic adjustment of vocational-school majors requires quantitative modeling of the relationship between professional supply and industrial skill demand. Conventional experience-based judgments and static statistics cannot capture rapid changes in labor-market requirements. This study proposes a big-data-supported analysis model for matching vocational majors with industry needs. Recruitment data and curriculum-system data are collected and transformed into a unified skill-tagging space. Natural-language-processing methods extract job-skill requirements from recruitment texts, and TF-IDF weighting is used to construct industry demand vectors. Professional curriculum features are mapped into supply-capability vectors according to course hours, course type, and competency objectives. A weighted cosine-similarity model and multi-indicator fusion mechanism are then built to evaluate skill matching, job coverage, and demand-intensity matching. A time-series updating mechanism further tracks dynamic changes in matching degree. Experimental results based on recruitment postings and vocational-college curriculum data show clear differentiation among majors: big data technology and nursing achieve high matching degrees of 0.85 and 0.83, while accounting shows a structural mismatch with a matching degree of 0.68. The proposed model supports semantic vectorization, industrial-demand sensing, and data-driven decision support for professional-structure optimization.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
References
K. Dong, L. Chen, and J. Wu, “Research on Intelligent Service System for Industrial Intelligence Driven by Innovation Demand,” Journal of Xihua University (Philosophy and Social Sciences Edition), vol. 45, no. 1, pp. 34-45, 2026.
Q. Yu, F. Zheng, and X. Lin, “Construction and Empirical Study of Supply and Demand Matching Model in my country’s Traditional Sports Consumption Market,” Journal of Shanghai University of Sport, vol. 49, no. 5, pp. 63-75, 2025.
X. Niu, J. Zhou, Y. Shi, et al., “Integration of professional expertise and innovation: an innovative path to break through the talent bottleneck in the integrated circuit industry,” Science and Technology Entrepreneurship Monthly, vol. 39, no. 2, pp. 25-30, 2026.
J. An, M. Yang, and C. Zhang, “The Logic and Path of Professional Setting in Higher Vocational Education under the Background of Industrial Restructuring,” Vocational Education, vol. 23, no. 06, pp. 15-19, 2024.
D. Wang, “An Exploration of the Adaptive Development of Industrial Demand and Human Capital Supply,” Studies on Socialism with Chinese Characteristics, vol. 6, no. 2, pp. 100-109, 2024.
M. Zou and M. Xu, “Research on the Path to Improve the Quality of Professional Construction in Modern Industry Colleges under the Background of “Dual-Wheel Drive” - From the Perspective of the Synergy between Engineering Education Professional Certification and Industry Demand,” Journal of Modern Education, vol. 1, no. 3, pp. 108-120, 2025.
P. Cheng and L. Yang, “Research on the path of industry-education integration under the demand guidance of additive manufacturing industry,” Education Research and Practice, vol. 1, no. 1, pp. 1-4, 2025.
Y. Zhang, “Research on the Construction of Practical Teaching System for Tourism Management Major in Higher Vocational Colleges Based on Enterprise Talent Needs,” Journal of Jiangxi Electric Power Vocational and Technical College, vol. 36, no. 7, pp. 37-39, 2023.