Multi-source data fusion study in scientometrics

被引：4
作者：
Hai-Yun Xu
Zeng-Hui Yue
Chao Wang
Kun Dong
Hong-Shen Pang
Zhengbiao Han
机构：
[1] Chengdu Library of Chinese Academy of Sciences,School of Medical Information Engineering
[2] Jining Medical University,Guangzhou Institutes of Biomedicine and Health
[3] Chinese Academy of Sciences,undefined
[4] Nanjing Agricultural University,undefined
来源：
Scientometrics | 2017年 / 111卷
关键词：
Data fusion; Relations fusion; Multi-mode analysis; Multi-source data; Scientometrics;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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页码：773 / 792
页数：19
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