Multi-source Data Fusion
Multi-Source Data Fusion is a computational methodology that integrates heterogeneous data from multiple independent sources to generate a more accurate, consistent, and comprehensive representation of structural damage in post-earthquake assessment through the synergistic combination of complementary information.
982
Publications
34.2K
Citations
4.4K
Authors
1.1K
Institutions
Publications per year
2017–2026
850
982
Resolving conflicts in heterogeneous data by truth discovery and source reliability estimation
Qi Li, Yaliang Li, Jing Gao et al. · 2014 · 491 citations
Thomas M. Achenbach · Current Directions in Psychological Science · 2006 · 346 citations
1–5 of 982
4.4K
University at Buffalo, State University of New York, United States
5 publications · 637 citations
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4
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Xinjiang Technical Institute of Physics & Chemistry, China
4 publications · 148 citations
4
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1–5 of 4.4K
1.1K

Chinese Academy of Sciences
Beijing, China
30 h-index
75 publications
2.8K citations
Wuhan University
Wuhan, China
24 h-index
49 publications
2.2K citations
University of Chinese Academy of Sciences
Beijing, China
22 h-index
36 publications
1.3K citations

Southeast University
Nanjing, China
18 h-index
24 publications
1.2K citations

Harbin Institute of Technology
Harbin, China
17 h-index
21 publications
936 citations

Northwestern Polytechnical University
Xi'an, China
16 h-index
20 publications
664 citations
China University of Mining and Technology
Xuzhou, China
15 h-index
19 publications
660 citations
Aerospace Information Research Institute
Beijing, China
15 h-index
20 publications
646 citations
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58 publications · 1.7K citations
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18 publications · 976 citations
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20 publications · 719 citations
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16 publications · 308 citations
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13 publications · 869 citations
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