Jintao Tang

910 citations
51 papers · 453 indexed · h-index 11
Topics
Topic Modeling (16 papers)Complex Network Analysis Techniques (9 papers)Natural Language Processing Techniques (8 papers)
Partner nations
ChinaHong KongMalaysia

In The Last Decade

Jintao Tang

45 papers receiving 433 citations

Peers

Jintao Tang
Comparison fields: 5 of 78
  • Artificial Intelligence 184
  • Molecular Biology 125
  • Plant Science 99
  • Information Systems 69
  • Genetics 69
Replace Thierson Couto Rosa with:
Thierson Couto Rosa Brazil
Nádia Félix Felipe da Silva Brazil
Waleed Ammar United States
Laura Dietz United States
Daniela Pohl Austria
Oleg Rokhlenko United States
Riccardo Dondi Italy
Sylvie Ranwez France
Ioannis Karydis Greece
Junming Yin United States
Jintao Tang relative to Thierson Couto Rosa Brazil Thierson Couto Rosa's profile →
Citations per field
00.5×10×14.1×
Thierson Couto Rosa · 1×
Citations per year

Countries citing papers authored by Jintao Tang

Since Specialization
Citations

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

Fields of papers citing papers by Jintao Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jintao Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Jintao Tang. A scholar is included among the top collaborators of Jintao Tang 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 Jintao Tang. Jintao Tang 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
#WorkIndexed citations
1 0
2 0
3 2
4 0
5 1
6 1
7 20
8 10
9 13
10 20
11 3
12 3
13 22
14 43
15 10
16 52
17 10
18 7
19 10
20
Reducing Semantic Bias of Annotations for Semantic Web Service Discovery
1

About Jintao Tang

Jintao Tang is a scholar working on Artificial Intelligence, Computer Science Applications and Statistical and Nonlinear Physics, having authored 51 papers that have together received 453 indexed citations. Recurring topics across this work include Topic Modeling (16 papers), Complex Network Analysis Techniques (9 papers) and Natural Language Processing Techniques (8 papers). The work is most often cited by research in Artificial Intelligence (184 citations), Statistical and Nonlinear Physics (67 citations) and Computer Science Applications (22 citations). Jintao Tang has collaborated with scholars based in China, Hong Kong and Malaysia. Frequent co-authors include Shasha Li, Ting Wang, Miles Osborne, Zhunchen Luo, Yao‐Guang Liu, Letian Chen, Yongyao Xie, Ting Wang, Ji Wang and Baixiao Niu. Their work appears in journals such as Nature Communications, Expert Systems with Applications and IEEE Access.

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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