Cong Wang

1.3k citations
105 papers · 1.0k · h-index 19

Impact in

Papers in

    • Advanced Text Analysis Techniques 11
    • Text and Document Classification Technologies 7
    • Natural Language Processing Techniques 7
    • Topic Modeling 6
    • Web Data Mining and Analysis 13
    • Service-Oriented Architecture and Web Services 6

Cong Wang

95 papers receiving 982 citations

Peers

Cong Wang
Comparison fields: 5 of 109
  • Artificial Intelligence 478
  • Computer Networks and Communications 281
  • Information Systems 228
  • Computer Vision and Pattern Recognition 183
  • Signal Processing 89
Replace Sayan Ghosh with:
Sayan Ghosh United States
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Fengli Zhang China
Lu Zhou China
Sudhakar Kumar India
Hiroshi Esaki Japan
Imran Memon China
Benxiong Huang China
Kangfeng Zheng China
Jialiang Peng China
Cong Wang relative to Sayan Ghosh United States Sayan Ghosh's profile →
Citations per field
00.5×1.5×
Sayan Ghosh · 1×
Citations per year

Countries citing papers authored by Cong Wang

Since Specialization
Citations

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

Fields of papers citing papers by Cong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 105 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201669
2 201464
3 201350
4 201849
5 201643
6 201541
7 201241
8 201332
9 201331
10 201826
11 201825
12 201625
13 201822
14 201922
15 200821
16 201721
17 201921
18 202019
19 201319
20 200618

About Cong Wang

Cong Wang is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Computer Vision and Pattern Recognition and Signal Processing, having authored 105 papers that have together received 1.0k indexed citations. Recurring topics across this work include Web Data Mining and Analysis (13 papers), Advanced Text Analysis Techniques (11 papers), Network Security and Intrusion Detection (8 papers), Text and Document Classification Technologies (7 papers), Natural Language Processing Techniques (7 papers), Topic Modeling (6 papers), Advanced Algorithms and Applications (6 papers) and Service-Oriented Architecture and Web Services (6 papers). The work is most often cited by research in Artificial Intelligence (478 citations), Computer Networks and Communications (281 citations), Information Systems (228 citations), Computer Vision and Pattern Recognition (183 citations) and Signal Processing (89 citations). Cong Wang has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Yixian Yang, Gang Xu, Zhibo Pang, Kai Kang, Lixiang Li, Wenhua Shao, Haiyong Luo, Fang Zhao, Jianyi Liu and Haipeng Peng. Their work appears in journals such as Quantum Information Processing, IEEE Access, Chaos Solitons & Fractals, Pattern Recognition Letters and IEEE Transactions on Industrial Informatics.

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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