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Multi-source data fusion study in scientometrics

delete2017-02-15
delete17
PRE
AI
H
Haiyun Xu *
Z
Zenghui Yue
王超 (Chao Wang)
董坤 cover
董坤 (Kun Dong)
H
Hongshen Pang
Z
Zhengbiao Han
DOI:10.1007/s11192-017-2290-5delete
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Abstract

Abstract

En 中文
This paper provides an introduction to multi-source data fusion (MSDF) and comprehensively overviews the ingredients and challenges of MSDF in scientometrics. As compared to the MSDF methods in the sensor and other fields, and considering the features of scientometrics, in this paper an application model and procedure of MSDF in scientometrics are proposed. The model and procedure can be divided into three parts: data type integration, fusion of data relations, and ensemble clustering. Furthermore, the fusion of data relations can be divided into cross-integration of multi-mode data and matrix fusion of multi-relational data. To obtain a clearer and deeper analysis of the MSDF model, this paper further focuses on the application of MSDF in topic identification based on text analysis of scientific literatures. This paper also discusses the application of MSDF for the exploration of scientific literatures. Finally, the most suitable MSDF methods for different situations are discussed.
Keywords:
Data fusion
Relations fusion
Multi-mode analysis
Multi-source data
Scientometrics
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Journal

Scientometrics cover
Scientometrics
IF:
3.5
Papers:
8.1K
Citations:
2.2W

Organization

J
Jining Medical University
Scholars:
4.1K
Papers: 2.2K
Citations: 2.9K
G
guangzhou institute of biomedicine & health, cas
Scholars:
1.1K
Papers: 685
Citations: 1
C
chinese academy of sciences
Scholars:
56.2W
Papers: 44.8W
Citations: 704
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