Research on the Construction of Personalized Employment Guidance Service Model in Colleges and Universities under the Background of Big Data

With the popularization of higher education and the increasing number of graduates, the employment of college students has become the focus of social attention. However, at present, the traditional employment guidance methods used by colleges and universities still rely on empirical judgment and manual matching, which is difficult to meet the increasingly diversified needs of students and the rapidly changing job market, and faces problems such as asymmetric information, uneven distribution of resources and low service accuracy. In this regard, according to the current situation of employment guidance in colleges and universities, this paper will deeply explore the application feasibility of big data technology in this field, and propose a brand-new personalized employment guidance service model to promote the upgrading of employment guidance from empirical to scientific. Practice has proved that all the advantages of big data technology, such as massive data processing ability, accurate analysis and prediction, personalized service and efficient matching, can provide new ideas and directions for college students’ employment guidance, which is of great significance for improving the efficiency and quality of employment guidance and promoting students’ career development.