Xiaotao Gu

901 citations
19 papers · 378 indexed · h-index 9
Topics
Topic Modeling (13 papers)Natural Language Processing Techniques (8 papers)Advanced Graph Neural Networks (6 papers)
Journals
IEEE Transactions on Knowledge and Data EngineeringSocial Network Analysis and MiningProceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Partner nations
United StatesChinaCanada

In The Last Decade

Xiaotao Gu

18 papers receiving 365 citations

Peers

Xiaotao Gu
Comparison fields: 5 of 44
  • Artificial Intelligence 349
  • Information Systems 69
  • Management Science and Operations Research 57
  • Computer Vision and Pattern Recognition 54
  • Molecular Biology 40
Replace Yee Fan Tan with:
Yee Fan Tan Singapore
Mojtaba Nayyeri Germany
Arzoo Katiyar United States
Joachim Daiber Netherlands
Luciano Del Corro Germany
Xisen Jin United States
Octavian-Eugen Ganea Switzerland
Shanchan Wu United States
Shib Sankar Dasgupta United States
Julien Kloetzer Japan
Xiaotao Gu relative to Yee Fan Tan Singapore Yee Fan Tan's profile →
Citations per field
00.5×7.2×
Yee Fan Tan · 1×
Citations per year

Countries citing papers authored by Xiaotao Gu

Since Specialization
Citations

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

Fields of papers citing papers by Xiaotao Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaotao Gu

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaotao Gu. A scholar is included among the top collaborators of Xiaotao Gu 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 Xiaotao Gu. Xiaotao Gu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
#WorkIndexed citations
1 1
2 0
3 4
4 3
5 1
6 7
7 17
8 27
9 4
10 29
11 35
12 52
13 132
14 10
15 29
16 1
17 22
18 3
19 1

About Xiaotao Gu

Xiaotao Gu is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Vision and Pattern Recognition, having authored 19 papers that have together received 378 indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Natural Language Processing Techniques (8 papers) and Advanced Graph Neural Networks (6 papers). The work is most often cited by research in Artificial Intelligence (349 citations), Management Science and Operations Research (57 citations) and Information Systems (69 citations). Xiaotao Gu has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Xiang Ren, Jiawei Han, Liyuan Liu, Jingbo Shang, Yuning Mao, Yuxiao Dong, Hongkun Yu, Jie Tang, Yan Wang and Rui Li. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Social Network Analysis and Mining and Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

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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