Kai Shuang

1.8k citations
93 papers · 1.2k indexed · h-index 20
Topics
Topic Modeling (24 papers)Caching and Content Delivery (20 papers)Natural Language Processing Techniques (15 papers)

In The Last Decade

Kai Shuang

84 papers receiving 1.2k citations

Peers

Kai Shuang
Comparison fields: 5 of 93
  • Computer Networks and Communications 718
  • Information Systems 513
  • Artificial Intelligence 343
  • Electrical and Electronic Engineering 271
  • Computer Vision and Pattern Recognition 179
Replace Dongman Lee with:
Dongman Lee South Korea
Naranker Dulay United Kingdom
G.-C. Roman United States
Junde Song China
Étienne Rivière Switzerland
Paolo Arcaini Japan
Himanshu Gupta India
Claudio Soriente United States
Jonathan Ledlie United States
Sanjeev Kulkarni United States
Kai Shuang relative to Dongman Lee South Korea Dongman Lee's profile →
Citations per field
00.5×3.2×
Dongman Lee · 1×
Citations per year

Countries citing papers authored by Kai Shuang

Since Specialization
Citations

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

Fields of papers citing papers by Kai Shuang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kai Shuang

This figure shows the co-authorship network connecting the top 25 collaborators of Kai Shuang. A scholar is included among the top collaborators of Kai Shuang 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 Kai Shuang. Kai Shuang 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
1 1
2 0
3 2
4 0
5 1
6 9
7 4
8 3
9 7
10 7
11
Neuron-level Structured Pruning using Polarization Regularizer
40
12 23
13 3
14 2
15 2
16 88
17 0
18 6
19 1
20
Towards Autonomic Semantic Web Services Selection with Heterogeneous QoS Values and Uncertain User Weights.
3

About Kai Shuang

Kai Shuang is a scholar working on Computer Networks and Communications, Computational Mathematics and Information Systems, having authored 93 papers that have together received 1.2k indexed citations. Recurring topics across this work include Topic Modeling (24 papers), Caching and Content Delivery (20 papers) and Natural Language Processing Techniques (15 papers). The work is most often cited by research in Computer Networks and Communications (718 citations), Information Systems (513 citations) and Hardware and Architecture (78 citations). Kai Shuang has collaborated with scholars based in China, United Kingdom and Switzerland. Frequent co-authors include Sen Su, Jonathan Loo, Zhongbao Zhang, Qingjia Huang, Jian Li, Peng Xu, Fangchun Yang, Yan Luo, Xiang Cheng and Zhixuan Zhang. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Sensors.

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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