Open Access iconOpen Access

ARTICLE

crossmark

Task-Oriented Battlefield Situation Information Hybrid Recommendation Model

Chunhua Zhou*, Jianjing Shen, Xiaofeng Guo, Zhenyu Zhou

PLA Strategic Support Force Information Engineering University, Zhengzhou, 450000, China

* Corresponding Author: Chunhua Zhou. Email: email

Intelligent Automation & Soft Computing 2021, 27(1), 127-141. https://doi.org/10.32604/iasc.2021.012532

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 information and combat tasks from auxiliary information. The results are predicted through logistic regression. To solve the multi-source heterogeneity of battlefield situation information, we design a hybrid learning and presentation model that integrates multiple deep learning models such as Doc2Vec, fully connected network and convolutional neural network (CNN), to integrate the rich and diverse data information in situational awareness system effectively. We perform experiments with the maneuvers dataset to test and evaluate the model through scenario simulation.

Keywords


Cite This Article

APA Style
Zhou, C., Shen, J., Guo, X., Zhou, Z. (2021). Task-oriented battlefield situation information hybrid recommendation model. Intelligent Automation & Soft Computing, 27(1), 127-141. https://doi.org/10.32604/iasc.2021.012532
Vancouver Style
Zhou C, Shen J, Guo X, Zhou Z. Task-oriented battlefield situation information hybrid recommendation model. Intell Automat Soft Comput . 2021;27(1):127-141 https://doi.org/10.32604/iasc.2021.012532
IEEE Style
C. Zhou, J. Shen, X. Guo, and Z. Zhou "Task-Oriented Battlefield Situation Information Hybrid Recommendation Model," Intell. Automat. Soft Comput. , vol. 27, no. 1, pp. 127-141. 2021. https://doi.org/10.32604/iasc.2021.012532



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 1807

    View

  • 1087

    Download

  • 0

    Like

Share Link