Chang Su

1.9k citations
43 papers · 1.1k indexed · 1 hit paper · h-index 8
Topics
Natural Language Processing Techniques (18 papers)Topic Modeling (12 papers)Advanced Text Analysis Techniques (6 papers)

In The Last Decade

Chang Su

42 papers receiving 1.1k citations

Hit Papers

Federated Learning for Healthcare Informatics20202026202220242020250500750

Peers

Chang Su
Comparison fields: 5 of 125
  • Artificial Intelligence 730
  • Information Systems 173
  • Electrical and Electronic Engineering 161
  • Computer Networks and Communications 122
  • Health Informatics 121
Replace Abdullah Aman Khan with:
Abdullah Aman Khan China
Kishor Datta Gupta United States
Md. Saddam Hossain Mukta Bangladesh
Meenu Gupta India
Rajanikanth Aluvalu India
Mario Brčić Croatia
Theodora S. Brisimi United States
Ravinder Kumar India
Abdul Khader Jilani Saudagar Saudi Arabia
Malak Abdullah Jordan
Chang Su relative to Abdullah Aman Khan China Abdullah Aman Khan's profile →
Citations per field
00.5×1.7×
Abdullah Aman Khan · 1×
Citations per year

Countries citing papers authored by Chang Su

Since Specialization
Citations

This map shows the geographic impact of Chang Su'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 Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chang Su more than expected).

Fields of papers citing papers by Chang Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chang Su. 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 Su. The network helps show where Chang Su may publish in the future.

Co-authorship network of co-authors of Chang Su

This figure shows the co-authorship network connecting the top 25 collaborators of Chang Su. A scholar is included among the top collaborators of Chang Su based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chang Su. Chang Su is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
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Federated Learning for Healthcare Informaticsbreakdown →
821
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Interactive Attention for Semantic Text Matching.
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Using grammar patterns to evaluate semantic similarity for short texts
4

About Chang Su

Chang Su is a scholar working on Artificial Intelligence, Information Systems and Experimental and Cognitive Psychology, having authored 43 papers that have together received 1.1k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (18 papers), Topic Modeling (12 papers) and Advanced Text Analysis Techniques (6 papers). The work is most often cited by research in Health Informatics (121 citations), Artificial Intelligence (730 citations) and Health Information Management (43 citations). Chang Su has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Peter Walker, Benjamin S. Glicksberg, Jiang Bian, Jie Xu, Fei Wang, Shuangqi Li, Hongwen He, Pengfei Zhao, Xianzhong Xie and Yijiang Chen. Their work appears in journals such as Applied Energy, Neurocomputing and Applied Sciences.

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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