摘要
快递服务在给社会带来便利的同时,也潜在着安全隐患。如何主动地从海量快递数据中发现和挖掘有价值的信息,是快递企业和相关安全管理部门亟需解决的问题。基于数据—信息—知识—智慧(DIKW)的建设理念,设计了一套快递大数据态势感知架构。该架构有效融合了数据、算力、算法和知识,为智能态势感知提供支撑,并通过模式识别和态势预测两个案例,验证了架构的有效性。
Express service not only brings convenience to the society,but also leads to various potential safety hazards.Actively discovering and mining hidden information from massive express data becomes an urgent problem faced by express enterprises and safety management departments.Based on the conception of“Data-Information-Knowledge-Wisdom(DIKW)”,this paper proposes a novel situation awareness architecture.The architecture effectively integrates data,computing power,algorithms and knowledge to provide intelligent support for situation awareness.This paper verifies the architecture with two cases:pattern recognition and situation prediction,and achieves remarkable results.
出处
《信息技术与标准化》
2022年第6期84-88,共5页
Information Technology & Standardization
基金
云南省“放管服”基础研究计划“跨境网络空间安全多源数据综合平台及态势感知应用研究”,项目编号:202001BB050076
云南大学引进人才科研经费项目“基于知识图谱和时间序列的智能业务风控技术研究”。
关键词
态势感知
快递大数据
数据仓库
模式识别
态势预测
situation awareness
express big data
data warehouse
pattern recognition
situation prediction
