Journal of Jilin University (Information Science Edition) ›› 2022, Vol. 40 ›› Issue (1): 64-70.

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Hierarchical Clustering-Based Short-Term Prediction System for College Students’ Employment

LI Luyao   

  1. Graduate Work Department of the Party Committee, Xi’an Polytechnic University, Xi’an 710048, China
  • Received:2021-05-19 Online:2022-01-25 Published:2022-01-27

Abstract: In view of the employment problem of college students, the hierarchical clustering strategy is used as technical support to construct a short-term forecast of employment system. According to the amount of data to be mined, the distance metric between clusters is selected. A hierarchical clustering tree composed of clusters and sub-clusters is constructed. The clustering or splitting of the target data is completed. The relevant algorithm operation process in the hierarchical clustering algorithm module is constructed. And combining with the prediction system roles and responsibilities of users and administrators, the multiple system database entities is designed. A mapping model of the relationship between entities is established. In the experimental stage, based on the collected information about the previous graduates of a certain university, a hierarchical structure model of the employment destination composed of the target layer, the criterion layer and the program layer is obtained. By comparing the predicted results of the employment destination of the students of the school with the actual results, the accuracy rate and recall are combined. It can be seen from the numerical value of the rate index that the system has high prediction accuracy, and it can meet the application needs of short-term prediction of student employment.


Key words: hierarchical clustering, college students, employment destination, prediction system, database;distance metric between clusters

CLC Number: 

  • TP311