Tao Ge

1.8k total citations
45 papers, 876 citations indexed

About

Tao Ge is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Biomedical Engineering. According to data from OpenAlex, Tao Ge has authored 45 papers receiving a total of 876 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 7 papers in Biomedical Engineering. Recurrent topics in Tao Ge's work include Topic Modeling (27 papers), Natural Language Processing Techniques (22 papers) and Text Readability and Simplification (8 papers). Tao Ge is often cited by papers focused on Topic Modeling (27 papers), Natural Language Processing Techniques (22 papers) and Text Readability and Simplification (8 papers). Tao Ge collaborates with scholars based in China, United States and Canada. Tao Ge's co-authors include Baobao Chang, Furu Wei, Ming Zhou, Zhifang Sui, Wangchunshu Zhou, Canwen Xu, Sujian Li, Ke Xu, Lei Sha and Tingsong Jiang and has published in prestigious journals such as Sensors, Physics in Medicine and Biology and Medical Physics.

In The Last Decade

Tao Ge

40 papers receiving 828 citations

Peers

Tao Ge
Comparison fields: 5 of 99
  • Artificial Intelligence 678
  • Computer Vision and Pattern Recognition 183
  • Information Systems 80
  • Management Science and Operations Research 47
  • Accounting 28
Replace Dequan Zheng with:
Dequan Zheng China
Xiaochuan Ni China
Fahd S. Alotaibi Saudi Arabia
Rafał Dreżewski Poland
Donghyuk Shin United States
M. P. Sebastian India
Malek Alzaqebah Saudi Arabia
Jerzy Korczak Poland
Dequan Zheng China View profile →
Citations per field, relative to Tao Ge
Tao Ge · 1×
Citations per year, relative to Tao Ge
Tao Ge · 1×

Countries citing papers authored by Tao Ge

Since Specialization
Citations

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

Fields of papers citing papers by Tao Ge

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tao Ge

This figure shows the co-authorship network connecting the top 25 collaborators of Tao Ge. A scholar is included among the top collaborators of Tao Ge 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 Tao Ge. Tao Ge 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 13
2 0
3 1
4 31
5 1
6 6
7 22
8 100
9 2
10 5
11 48
12 65
13
Event Detection with Burst Information Networks
12
14
Towards Time-Aware Knowledge Graph Completion
47
15 5
16 16
17 0
18 98
19 6
20 0

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026