面向战场信息共享平台的个性化推荐研究  

Research on Personalized Recommendation for Battlefield Information Sharing Platform

作　　者：葛婉 刘思其 张捷[1] 杜宝珠 Ge Wan

机构地区：[1]南京理工大学自动化学院,江苏南京210000 [2]陆军装备部驻重庆地区第一军事代表室,重庆400000

出　　处：《工业控制计算机》2022年第2期121-123,共3页Industrial Control Computer

摘　　要：随着大数据技术的发展,信息化、智能化作战将成为现代战争的未来趋势,如何从浩瀚信息中获取有效信息是提高作战指挥效率的重要问题。面向战场信息共享平台,利用推荐系统可解决信息过载问题的优势,结合军事领域信息数据特点,构建军事平台的个性化推荐系统框架,然后基于该推荐系统,提出融合情景感知的推荐算法,以提高军事平台的推荐服务质量。With the development of big data technology,information-based and intelligent warfare will become the future trend of modern warfare.How to obtain effective information from vast information is an important issue to improve the efficiency of combat command.Based on the battlefield information sharing platform,this paper uses the advantages of the recommendation system that can solve the problem of information overload to construct the personalized recommendation system framework of the military platform.Then,based on the recommendation system,this paper proposes a recommendation algorithm that integrates context-aware,in order to improve the recommendation service quality of the military platform.

关 键 词：个性化推荐 情景感知 信息共享平台 

分 类 号：E91[军事] TP391.3[自动化与计算机技术—计算机应用技术]