Jun-Lin Lin

1.1k citations
42 papers · 813 indexed · h-index 17

Jun-Lin Lin

39 papers receiving 745 citations

Peers

Jun-Lin Lin
Comparison fields: 5 of 77
  • Management Science and Operations Research 231
  • Artificial Intelligence 421
  • Signal Processing 114
  • Computational Theory and Mathematics 134
  • Information Systems 162
Replace Khin Lwin with:
Khin Lwin United Kingdom
Sumitra Mukherjee United States
Mustafa Mat Deris Malaysia
Chun-Hao Chen Taiwan
Alan Tickle Australia
Yihua Chen China
Abdullah Balamash Saudi Arabia
Georg Peters Germany
Chien-Chung Chan United States
Parimala Thulasiraman Canada
Jun-Lin Lin relative to Khin Lwin United Kingdom Khin Lwin's profile →
Citations per field
00.5×6.8×
Khin Lwin · 1×
Citations per year

Countries citing papers authored by Jun-Lin Lin

Since Specialization
Citations

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

Fields of papers citing papers by Jun-Lin Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 18 scholars most cited alongside Jun-Lin 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 Jun-Lin Lin Line = papers co-authored together Jun-Lin Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20234
3 20211
4 202016
5 20181
6
Detecting Fraudsters in Online Auction Using Variations of Neighbor Diversity
20152
7 20151
8 20141
9 20147
10 20134
11 20125
12 201217
13 20107
14 201054
15 201036
16 200939
17 200861
18 20087
19 20021
20 200250

About Jun-Lin Lin

Jun-Lin Lin is a scholar working on Signal Processing, Artificial Intelligence, Management Science and Operations Research, Computational Theory and Mathematics and Information Systems, having authored 42 papers that have together received 813 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (8 papers), Imbalanced Data Classification Techniques (7 papers), Data Management and Algorithms (7 papers), Data Mining Algorithms and Applications (6 papers), Rough Sets and Fuzzy Logic (6 papers), Cryptography and Data Security (6 papers), Fuzzy Logic and Control Systems (5 papers) and Stock Market Forecasting Methods (4 papers). The work is most often cited by research in Management Science and Operations Research (231 citations), Artificial Intelligence (421 citations), Signal Processing (114 citations), Computational Theory and Mathematics (134 citations) and Information Systems (162 citations). Jun-Lin Lin has collaborated with scholars based in Taiwan, United States and Thailand. Frequent co-authors include Pei‐Chann Chang, Margaret H. Dunham, Chin-Yuan Fan, Yan-Kuen Wu, Chen-Hao Liu, Celeste See-Pui Ng, Yu‐Chih Liu, Sy‐Ming Guu, Jui-Chien Hsieh and Yu‐Hsiang Tsai. Their work appears in journals such as Expert Systems with Applications, Symmetry, Energies, Distributed and Parallel Databases 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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