Young-Koo Lee
About
In The Last Decade
Young-Koo Lee
255 papers receiving 3.9k citations
Hit Papers
Peers
Comparison fields: 5 of 141
- Computer Vision and Pattern Recognition 1.5k
- Artificial Intelligence 1.5k
- Information Systems 1.3k
- Computer Networks and Communications 1.2k
- Signal Processing 623
Countries citing papers authored by Young-Koo Lee
This map shows the geographic impact of Young-Koo Lee'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 Young-Koo Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Young-Koo Lee more than expected).
Fields of papers citing papers by Young-Koo Lee
This network shows the impact of papers produced by Young-Koo Lee. 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 Young-Koo Lee. The network helps show where Young-Koo Lee may publish in the future.
Co-authorship network of co-authors of Young-Koo Lee
This figure shows the co-authorship network connecting the top 25 collaborators of Young-Koo Lee. A scholar is included among the top collaborators of Young-Koo Lee 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 Young-Koo Lee. Young-Koo Lee 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 | 0 | |
| 3 | 72 | |
| 4 | 1 | |
| 5 | Redundant Operation Reduction Technique on Repeated Mining of Frequent Subgraphs | 0 |
| 6 | Cloud Computing for Healthcare IT Infrastructure | 0 |
| 7 | Graph Model based Activity Pattern Mining for Healthcare | 2 |
| 8 | Analyzing Association Rule Mining and Clustering on Sales Day Data with XLMiner and Weka | 7 |
| 9 | Using Sensor Sequences for Activity Recognition by Mining and Multi-Class Adaboost. | 3 |
| 10 | Modified SHA-1 hash function (mSHA-1) | 5 |
| 11 | Results in Stress Test in the Ankle Stability of Young Men in Korea | 1 |
| 12 | ShrFP-tree: an efficient tree structure for mining share-frequent patterns | 2 |
| 13 | Complications after Total Ankle Replacement Arthroplasty | 2 |
| 14 | Results in Conservative Treatment of Osteochondral Lesion of Talus | 2 |
| 15 | Viewer Perception of Superellipsoid-based Accelerometer Visualization Techniques. | 1 |
| 16 | Proximal Metatarsal Chevron Osteotomy for Moderate to Severe Hallux Valgus: A Mean Eight Year Follow up | 2 |
| 17 | A Research Framework Model to Guide Both Broad and Focused Research into Ubiquitous Sensor Networks. | 0 |
| 18 | A Novel Hybrid Neural Network for Data Clustering. | 1 |
| 19 | 9 | |
| 20 | A Region Splitting Strategy for Physical Database Design of Multidimensional File Organizations | 15 |
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.