Ruiming Tang

7.2k citations
150 papers · 2.2k indexed · 1 hit paper · h-index 26
Topics
Recommender Systems and Techniques (113 papers)Advanced Graph Neural Networks (46 papers)Topic Modeling (44 papers)
Partner nations
ChinaHong KongCanada

In The Last Decade

Ruiming Tang

137 papers receiving 2.1k citations

Hit Papers

How Can Recommender Systems Benefit from Large Language M...20242026202520241020304050

Peers

Ruiming Tang
Comparison fields: 5 of 84
  • Information Systems 1.6k
  • Artificial Intelligence 1.4k
  • Computer Vision and Pattern Recognition 548
  • Management Science and Operations Research 483
  • Computer Networks and Communications 205
Replace Xiuqiang He with:
Xiuqiang He China
Vihan Jain United States
Xiaoqiang Zhu China
Ying Fan China
Jeremiah Harmsen United States
Wenwu Ou China
Dawei Yin China
Peng Jiang China
Huifeng Guo China
Huan Zhao China
Ruiming Tang relative to Xiuqiang He China Xiuqiang He's profile →
Citations per field
00.5×1.5×2.3×
Xiuqiang He · 1×
Citations per year

Countries citing papers authored by Ruiming Tang

Since Specialization
Citations

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

Fields of papers citing papers by Ruiming Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruiming Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Ruiming Tang. A scholar is included among the top collaborators of Ruiming 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 Ruiming Tang. Ruiming 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 1
3 0
4 4
5 0
6 1
7 6
8
How Can Recommender Systems Benefit from Large Language Models: A Surveybreakdown →
53
9 36
10 1
11 2
12 47
13 9
14 16
15 1
16 2
17 8
18 6
19 1
20 7

About Ruiming Tang

Ruiming Tang is a scholar working on Information Systems, Artificial Intelligence and Management Science and Operations Research, having authored 150 papers that have together received 2.2k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (113 papers), Advanced Graph Neural Networks (46 papers) and Topic Modeling (44 papers). The work is most often cited by research in Information Systems (1.6k citations), Artificial Intelligence (1.4k citations) and Management Science and Operations Research (483 citations). Ruiming Tang has collaborated with scholars based in China, Hong Kong and Canada. Frequent co-authors include Xiuqiang He, Huifeng Guo, Weinan Zhang, Yong Yu, Wei Guo, Yingxue Zhang, Bo Chen, Xinyi Dai, Weiwen Liu and Chen Ma. Their work appears in journals such as IEEE Access, Information Sciences and Neurocomputing.

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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