With the continuous development of information processing technology in modern society, the construction of intelligent campus has become an inevitable trend.As a new teaching mode, intelligent education is attracting more and more scholars and researchers' attention. The purpose of this paper is to study the modeling of personal portrait of students in intelligent campus of higher vocational colleges based on data mining algorithm. First of all, this paper introduces the characteristics of students' personal portraits, and expounds the factors that affect students' personal portraits. Then, the association rule algorithm is studied, and based on this algorithm, the personal portrait model of students in the intelligent campus of higher vocational colleges is designed. Finally, the function of the model is verified by simulation experiments. The test results show that the intelligent campus portrait model based on data mining algorithm has the characteristics of short data processing time, low delay time, high safety factor, and is compatible with the platform, indicating that the model functions well.

The application of big data in the Internet, cloud computing and other fields is becoming more and more extensive, with the continuous increase of the network environment and information resources of students' campuses, the network structure of university libraries has also undergone tremendous changes, and the amount of data storage has also become larger and larger. How to use massive data mining technology to effectively classify and analyze students' campus information has become an urgent problem to be solved. In this paper, we mainly study the modeling and profiling of college students' behavior characteristics based on big data analysis and predictive training set. Firstly, this paper studies the theoretical techniques related to big data, including data mining algorithms and behavioral profiling overviews. Secondly, the analysis of student behavior portraits was carried out; Finally, the fusion verification of the student behavior portrait model was carried out, and the experimental results were analyzed and summarized.