Research on multi-source heterogeneous big data fusion based on WSR

Authors

Aihua LI, School of Management Science and Engineering, Central University of Finance and Economics, Beijing 100081, ChinaFollow
Weijia XU, School of Management Science and Engineering, Central University of Finance and Economics, Beijing 100081, China
Yong SHI, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China CAS Research Center on Fictitious Economy and Data Science, Beijing 100190, China Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, ChinaFollow

Keywords

multi-source heterogeneous, wuli-shili-renli (WSR), data fusion, big data

Document Type

S & T and Society

Abstract

In the era of multi-source heterogeneous big data, big data presents new features such as cross, diversity and variability. The applications of big data in a wider range of fields have new requirements for data fusion. Under this background, the connotation of data fusion is enriched and expanded. The generalized data fusion includes the fusion of data resources, the fusion of model methods, and the fusion of decision-makers' knowledge and experience. This study analyzes the characteristics of multi-source heterogeneous data fusion at three different fusion levels: data level, information level and decision level, and discusses challenges for data fusion in storage, application and analysis technology, data management as well as value determination. What's more, corresponding suggestions are putted forward, which benefit for enterprises, government and other entities to effectively manage data resources and provide reference for more in-depth data fusion analysis.

First page

1225

Last Page

1233

Language

Chinese

Publisher

Bulletin of Chinese Academy of Sciences

References

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Recommended Citation

LI, Aihua; XU, Weijia; and SHI, Yong (2023) "Research on multi-source heterogeneous big data fusion based on WSR," Bulletin of Chinese Academy of Sciences (Chinese Version): Vol. 38 : Iss. 8 , Article 12.
DOI: https://doi.org/10.16418/j.issn.1000-3045.20220921003
Available at: https://bulletinofcas.researchcommons.org/journal/vol38/iss8/12