期刊文献+

基于数据融合的商务智能与分析架构研究 被引量:4

Framework of Business Intelligence and Analysis Based on Data Fusion
下载PDF
导出
摘要 商务智能与分析(BI&A)3.0的出现和信息融合应用场景的拓宽增强了数据融合在商务智能研究中的重要性。越来越多经济和管理领域的研究运用了融合的思想和方法,数据融合在这些领域的应用表现出了不同于传统信息融合的特点。从信息融合和BI&A出发,提出了多源异构大数据背景下基于数据融合视角的BI&A新内涵,突出了数据融合在商务智能分析过程中的重要性。基于WSR系统科学方法论构建了商务智能分析“数据、信息、知识”的融合架构,使数据融合能更好地应用于经济、金融和管理等领域,为从海量多源异构数据中获取知识提供了科学依据,有利于更有效的商务智能系统的研发和实现。 The emergence of business intelligence and analytics(BI&A)3.0 and the broadening application scenarios of information fusion enhance the importance of data fusion in the business intelligence.More and more researches in the fields of economy,finance and management use the idea and methods of fusion,and the application of data fusion in these fields shows characteristics different from the traditional information fusion.Considering the concepts of information fusion and BI&A,this paper puts forward the new connotation of BI&A based on the perspective of data fusion under the background of multi-source and heteroge-neous big data,highlighting the importance of data fusion in BI&A.In addition,the paper constructs the fusion framework of‘data,information and knowledge’for BI&A based on WSR system methodology,so that the data fusion can be better applied in the fields of economy,finance and management.It provides scientific basis for acquiring knowledge from massive multi-source and heterogeneous data,and is beneficial to the development and implementation of a more effective business intelligence system.
作者 李爱华 续维佳 石勇 LI Ai-hua;XU Wei-jia;SHI Yong(School of Management Science and Engineering,Central University of Finance and Economics,Beijing 100081,China;School of Economics and Management,University of Chinese Academy of Sciences,Beijing 100190,China;The Key Laboratory of Big Data Mining and Knowledge Management,Chinese Academy of Sciences,Beijing 100190,China)
出处 《计算机科学》 CSCD 北大核心 2022年第12期185-194,共10页 Computer Science
基金 国家自然科学基金(71932008) 中央财经大学新兴交叉学科建设项目。
关键词 商务智能 数据融合 多源异构数据 Business intelligence Data fusion Multi-source and heterogeneous data
  • 相关文献

参考文献14

二级参考文献170

共引文献640

同被引文献32

引证文献4

二级引证文献7

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部