Research on Optimization of Intelligent Recommendation System for College Employment Guidance Based on Deep Learning

To enhance the efficiency of employment guidance services in universities and improve the precision and personalization of job recommendations, a neural network-based intelligent recommendation system utilizing deep learning techniques was developed. By analyzing multidimensional data, including students' academic backgrounds, personal preferences, and market demands, an effective recommendation model was constructed. Experimental results indicate that the system achieved an accuracy rate exceeding 85%, significantly improving the alignment between students and job opportunities while enhancing the effectiveness of employment services. The findings demonstrate the potential and value of deep learning applications in university career guidance.