Xiaoxuan Shen

1.4k citations
38 papers · 915 indexed · 1 hit paper · h-index 12
Topics
Recommender Systems and Techniques (22 papers)Advanced Graph Neural Networks (15 papers)Topic Modeling (12 papers)
Partner nations
ChinaUnited States

In The Last Decade

Xiaoxuan Shen

31 papers receiving 896 citations

Hit Papers

EDMF: Efficient Deep Matrix Factorization With Review Fea...2021202620222024202150100150

Peers

Xiaoxuan Shen
Comparison fields: 5 of 96
  • Artificial Intelligence 495
  • Information Systems 456
  • Computer Vision and Pattern Recognition 247
  • Computer Science Applications 127
  • Computer Networks and Communications 69
Replace Hai Liu with:
Hai Liu China
Da Cao China
Arnab Nandi United States
Chugui Xu China
Lixin Han China
Guang Qiu China
Erheng Zhong Hong Kong
Tongqing Zhou China
Xiaoxuan Shen relative to Hai Liu China Hai Liu's profile →
Citations per field
00.5×1.5×2.0×
Hai Liu · 1×
Citations per year

Countries citing papers authored by Xiaoxuan Shen

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoxuan Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoxuan Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoxuan Shen. A scholar is included among the top collaborators of Xiaoxuan Shen 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 Xiaoxuan Shen. Xiaoxuan Shen 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 5
2 3
3 0
4 0
5 7
6 0
7 0
8 5
9 2
10 24
11 11
12 6
13 1
14 4
15 9
16 16
17 27
18 2
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EDMF: Efficient Deep Matrix Factorization With Review Feature Learning for Industrial Recommender Systembreakdown →
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About Xiaoxuan Shen

Xiaoxuan Shen is a scholar working on Computer Science Applications, Information Systems and Artificial Intelligence, having authored 38 papers that have together received 915 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (22 papers), Advanced Graph Neural Networks (15 papers) and Topic Modeling (12 papers). The work is most often cited by research in Computer Science Applications (127 citations), Information Systems (456 citations) and Artificial Intelligence (495 citations). Xiaoxuan Shen has collaborated with scholars based in China and United States. Frequent co-authors include Zhaoli Zhang, Baolin Yi, Hai Liu, Naixue Xiong, Sannyuya Liu, Jiangbo Shu, Duantengchuan Li, Jiazhang Wang, Ke Lin and Wei Zhang. Their work appears in journals such as Expert Systems with Applications, Information Sciences and Medicine.

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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