Kejia Chen

1.5k citations
67 papers · 928 · h-index 14

Impact in

Papers in

Kejia Chen

62 papers receiving 900 citations

Peers

Kejia Chen
Comparison fields: 5 of 133
  • Management Science and Operations Research 190
  • Statistical and Nonlinear Physics 94
  • Artificial Intelligence 239
  • Modeling and Simulation 31
  • Environmental Engineering 88
Replace William Guo with:
William Guo Australia
Paritosh Bhattacharya India
Fang Han United States
Yufeng Wang China
Gonzalo A. Ruz Chile
Zhipeng Zhang China
Emmanuel Gbenga Dada Nigeria
Jay Yellen United States
Hae-Sang Park South Korea
Pericles A. Mitkas Greece
Kejia Chen relative to William Guo Australia William Guo's profile →
Citations per field
00.5×4.3×
William Guo · 1×
Citations per year

Countries citing papers authored by Kejia Chen

Since Specialization
Citations

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

Fields of papers citing papers by Kejia Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015116
2 2017113
3 2006108
4 2004106
5 202180
6 201338
7
The GM Models That x(n) Be Taken as Initial Value
200232
8 201531
9 202120
10 200418
11 202116
12 201816
13 201314
14 201914
15 202213
16 201412
17 200812
18 202011
19 200811
20 201210

About Kejia Chen

Kejia Chen is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Information Systems and Management Science and Operations Research, having authored 67 papers that have together received 928 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (12 papers), Advanced Graph Neural Networks (12 papers), Domain Adaptation and Few-Shot Learning (5 papers), Recommender Systems and Techniques (5 papers), Grey System Theory Applications (5 papers), Text and Document Classification Technologies (4 papers), Opinion Dynamics and Social Influence (4 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Management Science and Operations Research (190 citations), Statistical and Nonlinear Physics (94 citations), Artificial Intelligence (239 citations), Modeling and Simulation (31 citations) and Environmental Engineering (88 citations). Kejia Chen has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Steve Granick, Bo Wang, Hongbin Dai, Jian Jin, Zhi‐Hua Zhou, Sifeng Liu, Yaoguo Dang, Yunyun Wang, Linfeng Liu and Yuanyuan Wang. Their work appears in journals such as Journal of Intelligent & Fuzzy Systems, Neurocomputing, Knowledge-Based Systems, ACM Transactions on Information Systems and Distributed and Parallel Databases.

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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