Limin Wang

788 citations
66 papers · 581 · h-index 14

Impact in

Papers in

Limin Wang

58 papers receiving 559 citations

Peers

Limin Wang
Comparison fields: 5 of 117
  • Artificial Intelligence 298
  • Management Science and Operations Research 89
  • Health Information Management 23
  • Computational Theory and Mathematics 70
  • Information Systems 74
Replace Yangguang Liu with:
Yangguang Liu China
Jiachen Liu China
André Luis Debiaso Rossi Brazil
Jin Gou China
Nandakishore Kambhatla United States
Yuchen Wu China
Saroj K. Meher India
Guilin Qi China
Limin Wang relative to Yangguang Liu China Yangguang Liu's profile →
Citations per field
00.5×3.4×
Yangguang Liu · 1×
Citations per year

Countries citing papers authored by Limin Wang

Since Specialization
Citations

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

Fields of papers citing papers by Limin Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201383
2 200653
3 201636
4 202025
5 202025
6 201621
7 201120
8 202018
9 202017
10 201415
11 201415
12 201615
13 201914
14 202114
15 201613
16 201712
17 201511
18 202110
19 20159
20 20199

About Limin Wang

Limin Wang is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Management Science and Operations Research, Information Systems and Molecular Biology, having authored 66 papers that have together received 581 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (41 papers), Rough Sets and Fuzzy Logic (15 papers), Data Quality and Management (14 papers), Machine Learning and Data Classification (12 papers), Data Mining Algorithms and Applications (10 papers), Imbalanced Data Classification Techniques (6 papers), Metabolomics and Mass Spectrometry Studies (6 papers) and Fault Detection and Control Systems (4 papers). The work is most often cited by research in Artificial Intelligence (298 citations), Management Science and Operations Research (89 citations), Health Information Management (23 citations), Computational Theory and Mathematics (70 citations) and Information Systems (74 citations). Limin Wang has collaborated with scholars based in China, Australia and Netherlands. Frequent co-authors include Minghui Sun, Shenglei Chen, Musa Mammadov, Chunhong Cao, Xiaolin Li, Geoffrey I. Webb, Ana María Martínez, Xiaowei Wang, Mooson Kwauk and Xinhua Liu. Their work appears in journals such as Applied Intelligence, IEEE Access, Knowledge-Based Systems, Knowledge and Information Systems and Expert Systems with Applications.

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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