摘要
财务共享服务中心利用采集的数据,通过对数据的处理、分析,挖掘出数据内隐藏的关联关系的技术随着信息技术的发展在不断完善.本文利用P(ρ,σ)-集合理论,得到P(ρ,σ)-数据结构及其属性依赖关系、颗粒度依赖关系与概率依赖关系,得到依属性、依颗粒度与依概率的P(ρ,σ)-数据的内分离-外融合的优选定理,并利用P(ρ,σ)-数据理论对财务共享服务数据处理进行了优化,给出了对搜集的原始数据依系统设定的概率进行冗余的数据删除的应用.
By the processing and analysing the financial data collected,the Financial Sharing Service Center tries to discover the association relationship hidden in them,and the techhnology is constantly improving with the development of information technology.In this paper,we propose the structure of P(ρ,σ)-data and derive its dependent relations of attribute dependency,the granularity dependency and the probability dependency based on P(ρ,σ)-sets.Forthermore,the optimization theorems of the internal separation-external fusion of the data are also obtained and applied to optimize the data processing of Enterprise Financial Sharing Service,which is illustrated by deleting redundant data in initial finacial data depending on given probability.
作者
冀娜
JI Na(Beijing Jiaotong University,Weihai Shandong 264200,China)
出处
《德州学院学报》
2020年第4期70-76,共7页
Journal of Dezhou University
基金
全国统计科学研究项目(2018LY14)
山东省统计科研基金重点资助项目(KT16253).
