集群化期刊平台智能决策数据仓库设计研究  

Research on the Design of Intelligent Decision Data Warehousefor Clustering Journal Platform

作　　者：张树瑜 ZHANG Shuyu(Shanghai Aerospace Control Technology Institute,Shanghai 201109,China)

机构地区：[1]上海航天控制技术研究所,上海201109

出　　处：《微型电脑应用》2023年第6期148-152,共5页Microcomputer Applications

摘　　要：集群化期刊平台智能决策支持系统开发不仅是期刊未来发展的必由之路,而且可以利用相关期刊论文进行大数据挖掘,为提升我国科研原始创新提供重要手段。通过我国期刊论文海量数据信息挖掘,并用智能算法生成各类表层之间的内在关系,通过“加工”实现数据的“增值”,以便及时、有效的为科研创新提供战略决策支持。这个决策支持系统采用的数据仓库技术具有诸多优点,能够弥补传统数据管理系统存在的与大数据分析架构不匹配、集成性和综合性较差等缺陷。文章从集群化期刊平台智能决策系统的现状及特点着手,分析并构建关于期刊平台集群化智能决策支持数据仓库的实现。The development of journal platform clustering intelligent decision support system is the only way for the future development of journals,and it is an effective use of big data to mine relevant journal papers,which can provide an important means for China to improve the original innovation of scientific research.Through the mining of massive data information in China's journal papers and the internal relationship between various surface layers generated by intelligent algorithms,the"processing"realizes the"value-added"of data,so as to provide strategic decision support for scientific research and innovation.The data warehouse technology is necessary for the decision support system,it can make up for the mismatch between the traditional data management system and the big data analysis architecture.It has many advantages to overcome defects in the application of intelligent decision support system,such as poor integration and comprehensiveness.This paper starts with the current situation and characteristics of the journal platform cluster intelligent decision support system,analyzes and constructs the realization of the journal platform cluster intelligent decision support data warehouse.

关 键 词：集群化期刊 数据仓库 多维模型 联机分析处理 大数据 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]