Hae‐Chang Rim
About
In The Last Decade
Hae‐Chang Rim
89 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 98
- Artificial Intelligence 1.1k
- Information Systems 439
- Molecular Biology 194
- Computer Vision and Pattern Recognition 122
- Sociology and Political Science 69
Countries citing papers authored by Hae‐Chang Rim
This map shows the geographic impact of Hae‐Chang Rim'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 Hae‐Chang Rim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hae‐Chang Rim more than expected).
Fields of papers citing papers by Hae‐Chang Rim
This network shows the impact of papers produced by Hae‐Chang Rim. 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 Hae‐Chang Rim. The network helps show where Hae‐Chang Rim may publish in the future.
Co-authorship network of co-authors of Hae‐Chang Rim
This figure shows the co-authorship network connecting the top 25 collaborators of Hae‐Chang Rim. A scholar is included among the top collaborators of Hae‐Chang Rim 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 Hae‐Chang Rim. Hae‐Chang Rim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 50 | |
| 2 | Translation Model Size Reduction for Hierarchical Phrase-based Statistical Machine Translation | 3 |
| 3 | Open Information Extraction for SOV Language Based on Entity-Predicate Pair Detection | 1 |
| 4 | Decoder-based Discriminative Training of Phrase Segmentation for Statistical Machine Translation | 1 |
| 5 | A Comparative Study on Optimal Feature Identification and Combination for Korean Dialogue Act Classification | 5 |
| 6 | Text-Confidence Feature Based Quality Evaluation Model for Knowledge Q&A Documents | 0 |
| 7 | A Corpus-based Hybrid Model for Morphological Analysis and Part-of-Speech Tagging | 1 |
| 8 | 1 | |
| 9 | Tree Tagging Tool using Two-phrase Parsing | 1 |
| 10 | Two-Phase Semantic Role Labeling based on Support Vector Machines | 6 |
| 11 | Title Named Entity Recognition based on Automatically Constructed Context Patterns and Entity Dictionary | 2 |
| 12 | Korea University Question Answering System at TREC 2004. | 6 |
| 13 | KUNLP system in Senseval-3 | 1 |
| 14 | 17 | |
| 15 | An Efficient Method for Korean Noun Extraction Using Noun Patterns | 2 |
| 16 | KUNLP System for NTCIR-3 English-Korean Cross-Language Information Retrieval | 3 |
| 17 | KUNLP system using Classification Information Model at SENSEVAL-2 | 3 |
| 18 | An Efficient Method for Korean Noun Extraction Using Noun Occurrence Characteristics. | 3 |
| 19 | 3 | |
| 20 | Part-of-Speech Tagging Using Complemental Characteristics of Linguistic Knowledge and Stochastic Information | 1 |
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.