Bei Shi

43 total papers · 1.3k total citations
22 papers, 714 citations indexed

About

Bei Shi is a scholar working on Artificial Intelligence, Sociology and Political Science and Information Systems. According to data from OpenAlex, Bei Shi has authored 22 papers receiving a total of 714 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 5 papers in Sociology and Political Science and 4 papers in Information Systems. Recurrent topics in Bei Shi's work include Topic Modeling (10 papers), Natural Language Processing Techniques (6 papers) and Artificial Intelligence in Games (5 papers). Bei Shi is often cited by papers focused on Topic Modeling (10 papers), Natural Language Processing Techniques (6 papers) and Artificial Intelligence in Games (5 papers). Bei Shi collaborates with scholars based in China, Hong Kong and United States. Bei Shi's co-authors include Wai Lam, Lidong Bing, Xin Li, Tengfei Shi, Deheng Ye, Qiang Fu, Lanxiao Huang, Liang Wang, Wei Yang and Peilin Zhao and has published in prestigious journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering and Management Accounting Research.

In The Last Decade

Bei Shi

21 papers receiving 697 citations

Hit Papers

Transformation Networks f... 2018 2026 2020 2023 2018 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Bei Shi 601 86 52 42 40 22 714
Shafaatunnur Hasan 425 0.7× 99 1.2× 93 1.8× 32 0.8× 41 1.0× 38 653
Jaime Carbonell 409 0.7× 80 0.9× 74 1.4× 20 0.5× 82 2.0× 24 636
Lin Yue 493 0.8× 52 0.6× 150 2.9× 91 2.2× 38 0.9× 30 723
Duncan A. J. Blythe 640 1.1× 62 0.7× 86 1.7× 46 1.1× 14 0.3× 14 848
Xiangyu Song 530 0.9× 158 1.8× 140 2.7× 56 1.3× 58 1.4× 28 732
Federica Bisio 527 0.9× 64 0.7× 108 2.1× 51 1.2× 45 1.1× 22 671
Maíra Gatti de Bayser 663 1.1× 72 0.8× 161 3.1× 59 1.4× 42 1.1× 20 803
Junjie Wu 331 0.6× 209 2.4× 101 1.9× 73 1.7× 70 1.8× 17 714
Miquel Ramírez 562 0.9× 162 1.9× 53 1.0× 24 0.6× 66 1.6× 35 723
Devendra Singh Chaplot 554 0.9× 379 4.4× 46 0.9× 31 0.7× 55 1.4× 28 901

Countries citing papers authored by Bei Shi

Since Specialization
Citations

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

Fields of papers citing papers by Bei Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bei Shi

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

All Works

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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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