Sang‐Wook Kim
- Artificial Intelligence top 1%
- Information Systems top 0.5%
- Signal Processing top 1%
- Computer Vision and Pattern Recognition top 2%
- Computer Networks and Communications top 2%
- Co-authors
- Dong‐Kyu ChaeSanghyun ParkWesley W. ChuYeon-Chang LeeSunju ParkDongwon LeeWonseok HwangBo Zhang
- Topics
- Recommender Systems and Techniques (70 papers)Complex Network Analysis Techniques (54 papers)Data Management and Algorithms (52 papers)
- Partner nations
- South KoreaUnited StatesChina
In The Last Decade
Sang‐Wook Kim
289 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 156
- Artificial Intelligence 1.3k
- Information Systems 1.3k
- Signal Processing 730
- Computer Vision and Pattern Recognition 598
- Computer Networks and Communications 465
Countries citing papers authored by Sang‐Wook Kim
This map shows the geographic impact of Sang‐Wook Kim'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 Sang‐Wook Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sang‐Wook Kim more than expected).
Fields of papers citing papers by Sang‐Wook Kim
This network shows the impact of papers produced by Sang‐Wook Kim. 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 Sang‐Wook Kim. The network helps show where Sang‐Wook Kim may publish in the future.
Co-authorship network of co-authors of Sang‐Wook Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Sang‐Wook Kim. A scholar is included among the top collaborators of Sang‐Wook Kim 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 Sang‐Wook Kim. Sang‐Wook Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | A Survey of Graph Neural Networks for Social Recommender Systemsbreakdown → | 56 |
| 6 | 3 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 4 | |
| 11 | 7 | |
| 12 | 5 | |
| 13 | 4 | |
| 14 | 2 | |
| 15 | A Comparative Study of Vector Space and Probabilistic Models in Computing Similarity of Scientific Papers | 0 |
| 16 | 3D Visualization of Close-Relationship among Smartphone Users | 2 |
| 17 | 4 | |
| 18 | Garbage Collection on the Embedded Java Virtual Machine | 0 |
| 19 | The Design and Development of MPEG-4 Contents Authoring System | 2 |
| 20 | A New Algorithm for Processing Joins Using the Multilevel Grid File | 6 |
About Sang‐Wook Kim
Sang‐Wook Kim is a scholar working on Signal Processing, Information Systems and Statistical and Nonlinear Physics, having authored 328 papers that have together received 3.0k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (70 papers), Complex Network Analysis Techniques (54 papers) and Data Management and Algorithms (52 papers). The work is most often cited by research in Signal Processing (730 citations), Information Systems (1.3k citations) and Artificial Intelligence (1.3k citations). Sang‐Wook Kim has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Dong‐Kyu Chae, Sanghyun Park, Wesley W. Chu, Yeon-Chang Lee, Sunju Park, Dongwon Lee, Wonseok Hwang, Bo Zhang, Jung‐Tae Lee and Jongwuk Lee. Their work appears in journals such as Applied Physics Letters, PLoS ONE and Cancer Research.
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.