Research on Prediction Model of College Students' Growth Based on Mobile Location Data Mining: Take Hunan Mass Media College as an example

With the rapid development of mobile internet technology, mobile terminal APP is closely related to the daily life of contemporary university students. This paper analyzes the algorithm of location data by obtaining the location data samples of university student terminal APP and defines the positions in semantics by obtaining the trajectory route of students' behavior. Analyze the daily behavior habits, social relationship, personal interests and hobbies and so on of university students by characteristics of university students' daily behaviors and the data of their moving tracks. In order to build a computational model for similarity of university students' user behavior to analyze the behavior of university students and induce four user types of university students with similar behaviors according to the classification of user behavior of university students by similarity calculation model. In order to carry out corresponding learning career planning guidance for different types of university students to establish a prediction model for the growth of university students which has been verified that it has a practical guiding significance by tests.