Yongsub Lim

15 papers receiving 284 citations

Peers

Yongsub Lim
Comparison fields: 5 of 51
  • Statistical and Nonlinear Physics 102
  • Computer Vision and Pattern Recognition 121
  • Signal Processing 58
  • Artificial Intelligence 153
  • Computer Networks and Communications 96
Replace Madhav Jha with:
Madhav Jha United States
Carlos H. C. Teixeira Brazil
Beixing Deng China
Jingbo Xu China
Mohsen A. M. El‐Bendary Egypt
Cheng‐Hsiung Yang Taiwan
Songjie Wei China
Xinzhe Fu United States
Anissa Sghaier Tunisia
Qixin Gao China
Yongsub Lim relative to Madhav Jha United States Madhav Jha's profile →
Citations per field
00.5×3.7×
Madhav Jha · 1×
Citations per year

Countries citing papers authored by Yongsub Lim

Since Specialization
Citations

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

Fields of papers citing papers by Yongsub Lim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Yongsub Lim, 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 Yongsub Lim Line = papers co-authored together Yongsub Lim links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 201495
2 201562
3
RaPP: Novelty Detection with Reconstruction along Projection Pathway
202026
4 201820
5 201913
6 201713
7 201512
8 20229
9 20198
10 20168
11 20117
12 20147
13 20146
14
Centrality Fairness: Measuring and Analyzing Structural Inequality of Online Social Network
20171
15 20131

About Yongsub Lim

Yongsub Lim is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Artificial Intelligence, Computer Networks and Communications and Signal Processing, having authored 15 papers that have together received 288 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (6 papers), Graph Theory and Algorithms (4 papers), Advanced Graph Neural Networks (4 papers), Data Management and Algorithms (3 papers), Advanced Database Systems and Queries (2 papers), Topological and Geometric Data Analysis (2 papers), Advanced Neural Network Applications (1 paper) and Electric Vehicles and Infrastructure (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (102 citations), Computer Vision and Pattern Recognition (121 citations), Signal Processing (58 citations), Artificial Intelligence (153 citations) and Computer Networks and Communications (96 citations). Yongsub Lim has collaborated with scholars based in South Korea, United Kingdom and Puerto Rico. Frequent co-authors include U Kang, Christos Faloutsos, Minsoo Jung, Ho‐Jin Choi, A. S. Yoon, Byungchan Kim, Ki‐Hyun Kim, Sangwoo Shim, Kyomin Jung and Pushmeet Kohli. Their work appears in journals such as World Wide Web, Data Mining and Knowledge Discovery, ACM Transactions on Knowledge Discovery from Data, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Access.

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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