• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science ›› 2022, Vol. 44 ›› Issue (08): 1364-1371.

• High Performance Computing • Previous Articles     Next Articles

A military training recommendation model based on Cross-DeepFM

GAO Yong-qiang1,ZHANG Zhi-ming1,WANG Yu-tao2   

  1. (1.College of Information Engineering,Engineering University of 
    the Chinese People’s Armed Police Force,Xi’an 710086;
    2.Guizhou Provincial Corps,the Chinese People’s Armed Police Force,Guiyang 550081,China)
  • Received:2021-10-13 Revised:2021-12-20 Accepted:2022-08-25 Online:2022-08-25 Published:2022-08-25

Abstract:  In order to apply the recommendation system to the field of military training and give full play to the value of military training big data in personalized training, a hybrid recommendation model called Cross-DeepFM is proposed. Firstly, the real military training data are collected and preprocessed, and the custom military training dataset is constructed. Then, the structure of the Cross-DeepFM model is designed by combining the deep residual neural network, deep cross network and factorization machine, and the details of the model are analyzed. Finally, the comparison and analysis are carried out on the custom military training data set. The experimental results show that the proposed model is more accurate than the mainstream recommendation model and can effectively complete the personalized recommendation task of military training.

Key words: military training, recommendation algorithm, deep learning, factorization machine