Application of big data analysis in college students' career interest identification and planning models

With the rapid development of big data technology, data analysis has become an essential tool in various industries. This paper explores the application of big data analysis in the identification and planning models of college students' career interests. By collecting and analyzing multidimensional data on college students' career interests, a big data-based career interest identification and planning model is established using data mining and machine learning algorithms. The research begins by comprehensively collecting data on students' personal information, academic performance, hobbies, personality traits, and more. Through data analysis, different career interest types among student groups are identified. Based on this data, the paper constructs a personalized career planning recommendation system aimed at providing more accurate career development advice and planning paths for college students. Through empirical analysis, the effectiveness of big data analysis in career interest identification and planning is validated, and it is pointed out that this method can significantly improve the scientific and rational nature of college students' career choices. Finally, the paper discusses the prospects of big data analysis in college students' career planning and outlines future research directions.