Multi-source data fusion study in scientometrics

Hai-Yun Xu (), Zeng-Hui Yue, Chao Wang, Kun Dong, Hong-Shen Pang and Zhengbiao Han
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Hai-Yun Xu: Chengdu Library of Chinese Academy of Sciences
Zeng-Hui Yue: Jining Medical University
Chao Wang: Chengdu Library of Chinese Academy of Sciences
Kun Dong: Chengdu Library of Chinese Academy of Sciences
Hong-Shen Pang: Chinese Academy of Sciences
Zhengbiao Han: Nanjing Agricultural University

Scientometrics, 2017, vol. 111, issue 2, No 10, 773-792

Abstract: Abstract 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 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11192-017-2290-5

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