Chang‐Dong Wang

7.9k citations
232 papers · 5.2k · 2 hit papers · h-index 41

Impact in

Papers in

Chang‐Dong Wang

207 papers receiving 5.2k citations

Chang‐Dong Wang's Hit Papers

Efficient Multi-View Clustering via Unified and Discrete Bipartite Graph Learning 2023 · 112 citations
1120+1+2Years since publication50100150

Peers

Chang‐Dong Wang
Comparison fields: 5 of 153
  • Computational Mathematics 163
  • Computer Vision and Pattern Recognition 2.8k
  • Artificial Intelligence 3.1k
  • Urban Studies 353
  • Media Technology 518
Replace Chun Chen with:
Chun Chen China
Yiu‐ming Cheung Hong Kong
Ling Huang China
Vikas Sindhwani United States
Zenglin Xu China
Chang Tang China
Benyu Zhang China
Jian Yin China
Jie Wen China
Zhongfei Zhang United States
Chang‐Dong Wang relative to Chun Chen China Chun Chen's profile →
Citations per field
00.5×4.6×
Chun Chen · 1×
Citations per year

Countries citing papers authored by Chang‐Dong Wang

Since Specialization
Citations

This map shows the geographic impact of Chang‐Dong Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chang‐Dong Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chang‐Dong Wang more than expected).

Fields of papers citing papers by Chang‐Dong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chang‐Dong Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chang‐Dong Wang. The network helps show where Chang‐Dong Wang may publish in the future.

Co-authors

The 25 scholars most cited alongside Chang‐Dong Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chang‐Dong Wang Line = papers co-authored together Chang‐Dong Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 232 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017259
2 2020216
3 2019166
4 2015165
5
Fast Multi-View Clustering Via Ensembles: Towards Scalability, Superiority, and Simplicity
Hit paper breakdown →
2023155
6 2015146
7 2015118
8 2019114
9
Efficient Multi-View Clustering via Unified and Discrete Bipartite Graph Learning
Hit paper breakdown →
2023112
10 2015109
11 201994
12 201892
13 201892
14 202291
15 202288
16 202287
17 202286
18 201982
19 201578
20 202068

About Chang‐Dong Wang

Chang‐Dong Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Statistical and Nonlinear Physics and Molecular Biology, having authored 232 papers that have together received 5.2k indexed citations. Recurring topics across this work include Face and Expression Recognition (61 papers), Advanced Graph Neural Networks (56 papers), Advanced Clustering Algorithms Research (53 papers), Recommender Systems and Techniques (49 papers), Complex Network Analysis Techniques (38 papers), Text and Document Classification Technologies (30 papers), Topic Modeling (23 papers) and Advanced Image and Video Retrieval Techniques (17 papers). The work is most often cited by research in Computational Mathematics (163 citations), Computer Vision and Pattern Recognition (2.8k citations), Artificial Intelligence (3.1k citations), Urban Studies (353 citations) and Media Technology (518 citations). Chang‐Dong Wang has collaborated with scholars based in China, United States and United Arab Emirates. Frequent co-authors include Jianhuang Lai, Dong Huang, Ling Huang, Philip S. Yu, Man-Sheng Chen, Hongyang Chao, Guangyu Zhang, Yumeng Xu, Yuren Zhou and Zhi‐Hong Deng. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering, Neurocomputing, Knowledge-Based Systems and Pattern Recognition.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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