Young-Sook Hwang
About
In The Last Decade
Young-Sook Hwang
20 papers receiving 293 citations
Peers
Comparison fields: 5 of 30
- Artificial Intelligence 310
- Molecular Biology 141
- Information Systems 20
- Computer Vision and Pattern Recognition 17
- Language and Linguistics 9
Countries citing papers authored by Young-Sook Hwang
This map shows the geographic impact of Young-Sook Hwang'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-Sook Hwang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Young-Sook Hwang more than expected).
Fields of papers citing papers by Young-Sook Hwang
This network shows the impact of papers produced by Young-Sook Hwang. 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-Sook Hwang. The network helps show where Young-Sook Hwang may publish in the future.
Co-authorship network of co-authors of Young-Sook Hwang
This figure shows the co-authorship network connecting the top 25 collaborators of Young-Sook Hwang. A scholar is included among the top collaborators of Young-Sook Hwang 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-Sook Hwang. Young-Sook Hwang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Phrase Segmentation Model using Collocation and Translational Entropy. | 1 |
| 2 | 15 | |
| 3 | Joint Tokenization and Translation | 14 |
| 4 | Better Filtration and Augmentation for Hierarchical Phrase-Based Translation Rules | 2 |
| 5 | Paraphrasing Depending on Bilingual Context Toward Generalization of Translation Knowledge. | 2 |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 11 | |
| 9 | 9 | |
| 10 | Nobody is Perfect: ATR's Hybrid Approach to Spoken Language Translation | 17 |
| 11 | Using Machine Translation Evaluation Techniques to Determine Sentence-level Semantic Equivalence. | 64 |
| 12 | Two-Phase Semantic Role Labeling based on Support Vector Machines | 6 |
| 13 | Bilingual Knowledge Extraction Using Chunk Alignment | 4 |
| 14 | 17 | |
| 15 | 78 | |
| 16 | 3 | |
| 17 | 70 | |
| 18 | 3 | |
| 19 | 3 | |
| 20 | 2 |
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.