Design of Personalized Employment Guidance System for College Students Based on Big Data

In view of the traditional system using personality test for employment guidance, which leads to one-sided guidance results, outdated system design architecture and low operation efficiency, this paper designs a personalized employment guidance system for college students based on big data. After designing the system hardware to collect the information of students’ employment environment, the system framework is designed based on B/S structure. Tptmf algorithm is used to recommend employment resources for users. After analyzing the system requirements, the database is designed to realize the system functions. The simulation results show that the response time of employment guidance system using big data is short, and the highest server occupation is only 11%, which is feasible.