摘要
面向大数据条件下的情报分析,从大数据处理平台和情报生成质量视角提出了一套情报大数据分析质量评估指标体系,针对指标体系建立了基于范数灰关联的情报大数据分析质量评估方法,并通过仿真实验验证了方法的有效性。该方法能够从多个视角对影响情报分析质量的因素进行综合分析,有效评判大数据条件下情报分析质量的优劣,能够为情报分析质量提高与优化提供支撑,以使指挥决策人员获取高质量的情报信息。
For the intelligence analysis under the condition of big data,this paper proposes the index system of intelligence big data analysis quality evaluation from the perspective of big data processing platform and intelligence generation quality.Based on the norm gray relational degree the intelligence big data analysis quality evaluation method is established for the index system.The effectiveness of the method is verified by simulation experiments.The method can comprehensively analyze the factors affecting the quality of intelligence analysis from multiple perspectives,and can provide support for the improvement and optimization of intelligence analysis,so that the commanders can obtain high-quality intelligence information.
作者
刘娜
陈健军
杨慧杰
李国栋
LIU Na;CHEN Jian-jun;YANG Hui-jie;LI Guo-dong(China Academy of Electronics and Information Technology,Beijing 100041,China)
出处
《中国电子科学研究院学报》
北大核心
2020年第1期55-62,共8页
Journal of China Academy of Electronics and Information Technology
基金
大数据条件下情报数据分析及使用的测试评估技术(16103601)。
关键词
情报分析质量
范数灰关联度
大数据
评估方法
quality of information analysis
norm gray relational degree
big data
evaluation method
