Factor Space, the Theoretical Base of Data Science

被引：1
|
作者：
Wang P.-Z. [1 ]
Liu Z.-L. [2 ]
Shi Y. [3 ]
Guo S.-C. [1 ]
机构：
[1] College of Intelligence Engineering and Mathematics, Liaoning Technical University, Fuxin
[2] National Defense University PLA China, Beijing
[3] Research Center of Fictitious Economy and Data Science, Chinese Academy of Science, Beijing
来源：
Annals of Data Science | 2014年 / 1卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Background relation; Factor space; Factor vane; Factorial databases; Factorial neural networks; Information fusion; Sample cultivation;
D O I：
10.1007/s40745-014-0017-5
中图分类号：
学科分类号：
摘要：
This paper introduces factor space theory, which provides a general coordinate system to describe the real world and a theoretical base for data science. Based on the theory, factorial databases is presented, which carries a new kind of statistics to do intelligent analysis for coming tide of Big Data. © 2014, Springer-Verlag Berlin Heidelberg.
引用
收藏
页码：233 / 251
页数：18
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