Wenya Wang

2.3k total citations · 1 hit paper
68 papers, 1.4k citations indexed

About

Wenya Wang is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Wenya Wang has authored 68 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Artificial Intelligence, 16 papers in Electrical and Electronic Engineering and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Wenya Wang's work include Topic Modeling (21 papers), Sentiment Analysis and Opinion Mining (12 papers) and Natural Language Processing Techniques (10 papers). Wenya Wang is often cited by papers focused on Topic Modeling (21 papers), Sentiment Analysis and Opinion Mining (12 papers) and Natural Language Processing Techniques (10 papers). Wenya Wang collaborates with scholars based in China, Singapore and United States. Wenya Wang's co-authors include Sinno Jialin Pan, Daniel Dahlmeier, Xiaokui Xiao, Qi Zhao, Jianwei Shuai, Li Zhang, Jianqiang Sun, Zhenfu Li, Yiwei Pan and Tianyun Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, Advanced Functional Materials and Chemical Engineering Journal.

In The Last Decade

Wenya Wang

57 papers receiving 1.4k citations

Hit Papers

Predicting the potential human lncRNA–miRNA interactions ... 2022 2026 2023 2024 2022 50 100 150

Peers

Wenya Wang
Comparison fields: 5 of 136
  • Artificial Intelligence 975
  • Molecular Biology 156
  • Electrical and Electronic Engineering 117
  • Information Systems 114
  • Computer Vision and Pattern Recognition 107
Replace Shuai Wang with:
Shuai Wang China
Jun Sakuma Japan
Muhammad Iqbal Pakistan
Qinke Peng China
Jiaoyan Chen China
Guangshun Li China
Hongbin Huang China
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Shuai Wang China View profile →
Citations per field, relative to Wenya Wang
Wenya Wang · 1×
Citations per year, relative to Wenya Wang
Wenya Wang · 1×

Countries citing papers authored by Wenya Wang

Since Specialization
Citations

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

Fields of papers citing papers by Wenya Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wenya Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Wenya Wang. A scholar is included among the top collaborators of Wenya Wang 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 Wenya Wang. Wenya Wang 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
# Work Indexed citations
1 0
2 1
3 1
4 1
5 1
6 0
7 1
8 2
9 11
10 6
11 2
12 11
13 42
14
Predicting the potential human lncRNA–miRNA interactions based on graph convolution network with conditional random field breakdown →
191
15 17
16 14
17
MetaQuant: Learning to Quantize by Learning to Penetrate Non-differentiable Quantization
13
18 16
19 260
20 10

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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