摘要
利用基于Hadoop生态的大数据平台,汇聚情报数据,通过对海上目标情报数据进行深度挖掘和关联分析,提升目标活动属性与关系信息挖掘能力,发现海上目标的活动路线、基本属性、事件类型、时间、区域等因素之间的多层隐性关联规则,从而实现对海上目标活动规律的精准分析、研判预测等功能。
This paper uses a Hadoop-based big data platform to gather intelligence data.Then,through in-depth mining and correlation analysis of maritime target intelligence data,the ability to mine target activity attributes and relationship information is improved.This paper studies the multi-layer implicit association rules among maritime target attributes,including activity routes,basic attributes,event types,time,areas,etc.Finally,the functions of precise analysis,judgment and prediction of the activity rules of maritime targets will be realized.
作者
郭鹏飞
李海霞
常海艳
白柯鑫
张煜
Guo Pengfei;Li Haixia;Chang Haiyan;Bai Kexin;Zhang Yu(North Automatic Control Technology Institute,Taiyuan 030006,China)
出处
《网络安全与数据治理》
2023年第S01期71-77,共7页
CYBER SECURITY AND DATA GOVERNANCE
