Shanshan Feng

2.5k citations
100 papers · 1.7k indexed · 1 hit paper · h-index 20
Topics
Recommender Systems and Techniques (22 papers)Topic Modeling (15 papers)Complex Network Analysis Techniques (15 papers)
Partner nations
ChinaSingaporeHong Kong

In The Last Decade

Shanshan Feng

94 papers receiving 1.6k citations

Hit Papers

Personalized ranking metric embedding for next new POI re...2015202620182022201550100150200

Peers

Shanshan Feng
Comparison fields: 5 of 105
  • Artificial Intelligence 722
  • Information Systems 538
  • Transportation 374
  • Computer Vision and Pattern Recognition 369
  • Statistical and Nonlinear Physics 183
Replace Liang Zhao with:
Liang Zhao United States
Song Chong South Korea
Guan Yuan China
Huy T. Vo United States
Tomoharu Iwata Japan
Huandong Wang China
Bo Han China
Stuart E. Middleton United Kingdom
Zhongmou Li United States
Zaher Al Aghbari United Arab Emirates
Shanshan Feng relative to Liang Zhao United States Liang Zhao's profile →
Citations per field
00.5×1.5×2.0×
Liang Zhao · 1×
Citations per year

Countries citing papers authored by Shanshan Feng

Since Specialization
Citations

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

Fields of papers citing papers by Shanshan Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shanshan Feng

This figure shows the co-authorship network connecting the top 25 collaborators of Shanshan Feng. A scholar is included among the top collaborators of Shanshan Feng 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 Shanshan Feng. Shanshan Feng 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 7
2 0
3 4
4 2
5 10
6 1
7 17
8 9
9 1
10 5
11 1
12 3
13 6
14 24
15 10
16 8
17 16
18 22
19 39
20 52

About Shanshan Feng

Shanshan Feng is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Modeling and Simulation, having authored 100 papers that have together received 1.7k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (22 papers), Topic Modeling (15 papers) and Complex Network Analysis Techniques (15 papers). The work is most often cited by research in Transportation (374 citations), Information Systems (538 citations) and Artificial Intelligence (722 citations). Shanshan Feng has collaborated with scholars based in China, Singapore and Hong Kong. Frequent co-authors include Gao Cong, Yeow Meng Chee, Xutao Li, Yunming Ye, Yifeng Zeng, Quan Yuan, Xutao Li, Billy Chiu, Jing Li and Bo An. Their work appears in journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Geoscience and Remote Sensing.

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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