Yiling Lin

59 papers receiving 635 citations

Peers

Yiling Lin
Comparison fields: 5 of 128
  • General Decision Sciences 18
  • Computer Science Applications 45
  • Accounting 66
  • Marketing 44
  • Management of Technology and Innovation 30
Replace Robert Pavur with:
Robert Pavur United States
Guang Yu China
Kesten C. Green Australia
Nate Silver United States
Catherine Dehon Belgium
James L. Corner New Zealand
An Chen China
Daniel K. N. Johnson United States
Robin L. Dillon United States
Sarah Gelper Belgium
Yiling Lin relative to Robert Pavur United States Robert Pavur's profile →
Citations per field
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Citations per year

Countries citing papers authored by Yiling Lin

Since Specialization
Citations

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

Fields of papers citing papers by Yiling Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yiling Lin, 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 Yiling Lin Line = papers co-authored together Yiling Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200770
2 201266
3 202159
4 201845
5 202136
6 200831
7 202025
8 201823
9 201422
10 202419
11 202219
12 201818
13 202315
14 201214
15 201314
16 201613
17 201312
18 201012
19 201311
20 20229

About Yiling Lin

Yiling Lin is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Science Applications and General Health Professions, having authored 63 papers that have together received 677 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (6 papers), Topic Modeling (5 papers), Information Retrieval and Search Behavior (5 papers), Primary Care and Health Outcomes (4 papers), Air Quality and Health Impacts (4 papers), Advanced Text Analysis Techniques (4 papers), Atmospheric chemistry and aerosols (4 papers) and Image Retrieval and Classification Techniques (4 papers). The work is most often cited by research in General Decision Sciences (18 citations), Computer Science Applications (45 citations), Accounting (66 citations), Marketing (44 citations) and Management of Technology and Innovation (30 citations). Yiling Lin has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Hsinchun Chen, Xin Li, Mihail C. Roco, Wen‐Min Lu, Wei‐Kang Wang, Ting‐Peng Liang, Peter Brusilovsky, I‐Han Hsiao, Magda Osman and Daqing He. Their work appears in journals such as Journal of Nanoparticle Research, Designs Codes and Cryptography, International Journal of Human-Computer Studies, Journal of the Association for Information Systems 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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