Yiling Lin

64 papers receiving 735 citations

Peers

Yiling Lin
Comparison fields: 5 of 125
  • General Decision Sciences 19
  • Computer Science Applications 56
  • Accounting 68
  • Health, Toxicology and Mutagenesis 66
  • Marketing 44
Replace Catherine Dehon with:
Catherine Dehon Belgium
Amanda M. Y. Chu Hong Kong
Guang Yu China
An Chen China
Kesten C. Green Australia
Haohui Chen Australia
Daniel K. N. Johnson United States
Robin L. Dillon United States
James L. Corner New Zealand
Yiling Lin relative to Catherine Dehon Belgium Catherine Dehon's profile →
Citations per field
00.5×3.1×
Catherine Dehon · 1×
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 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200776
2 201269
3 202163
4 201862
5 202140
6 200836
7 202029
8 201827
9 202423
10 202223
11 201422
12 201222
13 202321
14 201819
15 201615
16 201314
17 201314
18 201013
19 201312
20 202310

About Yiling Lin

Yiling Lin is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Science Applications and Computer Networks and Communications, having authored 70 papers that have together received 790 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (8 papers), Topic Modeling (5 papers), Atmospheric chemistry and aerosols (5 papers), Air Quality and Health Impacts (5 papers), Information Retrieval and Search Behavior (5 papers), Primary Care and Health Outcomes (4 papers), Advanced Text Analysis Techniques (4 papers) and Air Quality Monitoring and Forecasting (4 papers). The work is most often cited by research in General Decision Sciences (19 citations), Computer Science Applications (56 citations), Accounting (68 citations), Health, Toxicology and Mutagenesis (66 citations) and Marketing (44 citations). Yiling Lin has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Xin Li, Hsinchun Chen, Mihail C. Roco, Peter Brusilovsky, Wen‐Min Lu, Wei‐Kang Wang, Ting‐Peng Liang, I‐Han Hsiao, Magda Osman and Daqing He. Their work appears in journals such as International Journal of Human-Computer Studies, Atmosphere, Journal of Nanoparticle Research, Designs Codes and Cryptography and Journal of the Association for Information Systems.

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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