Chaofeng Sha

1.3k citations
39 papers · 648 · h-index 12

Impact in

Papers in

Chaofeng Sha

37 papers receiving 622 citations

Peers

Chaofeng Sha
Comparison fields: 5 of 57
  • Artificial Intelligence 402
  • Statistical and Nonlinear Physics 139
  • Computer Networks and Communications 249
  • Information Systems 231
  • Signal Processing 103
Replace Ravi Konuru with:
Ravi Konuru United States
Jiefeng Cheng Hong Kong
Yongzheng Zhang China
Dionysios Logothetis United States
Yantao Jia China
Gabriela Jacques-Silva United States
Venkatesan T. Chakaravarthy India
Kun‐Lung Wu United States
Ansley Post Germany
Jinqiao Shi China
Chaofeng Sha relative to Ravi Konuru United States Ravi Konuru's profile →
Citations per field
00.5×10×20×30.7×
Ravi Konuru · 1×
Citations per year

Countries citing papers authored by Chaofeng Sha

Since Specialization
Citations

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

Fields of papers citing papers by Chaofeng Sha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Chaofeng Sha, 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 Chaofeng Sha Line = papers co-authored together Chaofeng Sha links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018141
2 2003104
3 202285
4 202256
5 200745
6 202440
7
A framework for recommending relevant and diverse items
201627
8 202214
9 202213
10 202312
11 201612
12 200411
13 20129
14 20037
15 20037
16 20087
17 20236
18 20155
19 20144
20 20224

About Chaofeng Sha

Chaofeng Sha is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Computer Vision and Pattern Recognition and Signal Processing, having authored 39 papers that have together received 648 indexed citations. Recurring topics across this work include Software Engineering Research (8 papers), Topic Modeling (8 papers), Sentiment Analysis and Opinion Mining (5 papers), Software System Performance and Reliability (5 papers), Data Management and Algorithms (4 papers), Face and Expression Recognition (4 papers), Advanced Graph Neural Networks (4 papers) and Recommender Systems and Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (402 citations), Statistical and Nonlinear Physics (139 citations), Computer Networks and Communications (249 citations), Information Systems (231 citations) and Signal Processing (103 citations). Chaofeng Sha has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Aoying Zhou, Xin Huang, Li Ye, Yanchun Zhang, Xin Peng, Weining Qian, Jeffrey Xu Yu, Cheqing Jin, Chenxi Zhang and Bo Xu. Their work appears in journals such as Frontiers of Computer Science, Information Sciences, IEEE Transactions on Software Engineering, Knowledge-Based Systems and World Wide Web.

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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