Feng Xia

24 papers receiving 295 citations

Peers

Feng Xia
Comparison fields: 5 of 59
  • Information Systems 221
  • Management Science and Operations Research 103
  • Artificial Intelligence 155
  • Computer Vision and Pattern Recognition 77
  • Computer Science Applications 17
Replace Shijun Li with:
Shijun Li China
Flavian Vasile United States
Paolo Tomeo Italy
Diane Hu United States
Shuqing Bian China
Hengliang Luo China
Babak Loni Netherlands
Wendi Ji China
Hyunsouk Cho South Korea
Aniruddh Nath United States
Feng Xia relative to Shijun Li China Shijun Li's profile →
Citations per field
00.5×3.6×
Shijun Li · 1×
Citations per year

Countries citing papers authored by Feng Xia

Since Specialization
Citations

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

Fields of papers citing papers by Feng Xia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Feng Xia, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Feng Xia Line = papers co-authored together Feng Xia links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202160
2 202057
3
Curriculum Disentangled Recommendation with Noisy Multi-feedback
202127
4 202123
5 202218
6 201918
7 202316
8 202013
9 202111
10 20249
11 20208
12 20217
13 20226
14 20225
15 20234
16 20244
17 20144
18 20224
19 20233
20 20223

About Feng Xia

Feng Xia is a scholar working on Information Systems, Artificial Intelligence, Management Science and Operations Research, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 25 papers that have together received 306 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (15 papers), Advanced Bandit Algorithms Research (8 papers), Advanced Graph Neural Networks (7 papers), Caching and Content Delivery (3 papers), Advanced Neural Network Applications (2 papers), Multimodal Machine Learning Applications (2 papers), Topic Modeling (2 papers) and Image and Video Quality Assessment (2 papers). The work is most often cited by research in Information Systems (221 citations), Management Science and Operations Research (103 citations), Artificial Intelligence (155 citations), Computer Vision and Pattern Recognition (77 citations) and Computer Science Applications (17 citations). Feng Xia has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Ruobing Xie, Leyu Lin, Rui Wang, Shaoliang Zhang, Rui Wang, Yalong Wang, Yudong Chen, Wenwu Zhu, Xin Wang and Hong Chen. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Engineering Applications of Artificial Intelligence, ACM Transactions on Information Systems, Tectonophysics and Information Sciences.

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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