Chunhua Zhou*, Jianjing Shen, Xiaofeng Guo, Zhenyu Zhou
Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 127-141, 2021, DOI:10.32604/iasc.2021.012532
- 07 January 2021
Abstract In the process of interaction between users and battlefield situation information, combat tasks are the key factors that affect users’ information selection. In order to solve the problems of battlefield situation information recommendation (BSIR) for combat tasks, we propose a task-oriented battlefield situation information hybrid recommendation model (TBSI-HRM) based on tensor factorization and deep learning. In the model, in order to achieve high-precision personalized recommendations, we use Tensor Factorization (TF) to extract correlation relations and features from historical interaction data, and use Deep Neural Network (DNN) to learn hidden feature vectors of users, battlefield situation More >
Login
Register
