Abstract: Enhancing employment capabilities and selecting suitable career paths are crucial for deaf university students. The advancement of knowledge graph technology has opened up technical possibilities for career decision-making among these students. This paper calculates user preferences and introduces an exponential decay function integrated with a time factor to accurately reflect the dynamic changes in user interest preferences over time. Leveraging knowledge graphs for personalized recommendations, the study proposes recommending necessary skills to enhance employment and entrepreneurial capabilities among students. Additionally, it employs knowledge graphs to suggest more suitable career paths for deaf university students. Finally, through empirical validation, the paper demonstrates the effectiveness of the proposed hybrid clustering and interest-based collaborative filtering recommendation algorithm.

Pengyu Liu. “Research on the Path of Enhancing Employment and Entrepreneurship Ability of Deaf College Students Based on Knowledge Graph”. International Journal of Advanced Computer Science and Applications (IJACSA) 15.7 (2024). http://dx.doi.org/10.14569/IJACSA.2024.0150781

@article{Liu2024,
title = {Research on the Path of Enhancing Employment and Entrepreneurship Ability of Deaf College Students Based on Knowledge Graph},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150781},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150781},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {7},
author = {Pengyu Liu}
}