Ryohei Sasano
About
In The Last Decade
Ryohei Sasano
44 papers receiving 295 citations
Peers
Comparison fields: 5 of 45
- Artificial Intelligence 282
- Computer Vision and Pattern Recognition 48
- Information Systems 42
- Molecular Biology 11
- Management Science and Operations Research 11
Countries citing papers authored by Ryohei Sasano
This map shows the geographic impact of Ryohei Sasano'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 Ryohei Sasano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryohei Sasano more than expected).
Fields of papers citing papers by Ryohei Sasano
This network shows the impact of papers produced by Ryohei Sasano. 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 Ryohei Sasano. The network helps show where Ryohei Sasano may publish in the future.
Co-authorship network of co-authors of Ryohei Sasano
This figure shows the co-authorship network connecting the top 25 collaborators of Ryohei Sasano. A scholar is included among the top collaborators of Ryohei Sasano 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 Ryohei Sasano. Ryohei Sasano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | Development of a Medical Incident Report Corpus with Intention and Factuality Annotation. | 3 |
| 10 | 1 | |
| 11 | An Empirical Study on Fine-Grained Named Entity Recognition | 16 |
| 12 | 2 | |
| 13 | 12 | |
| 14 | Subtree Extractive Summarization via Submodular Maximization | 17 |
| 15 | Topic Estimation for Microblogs Taking into Account the Relationships between Adjacent Tweets | 1 |
| 16 | A Discriminative Approach to Japanese Zero Anaphora Resolution with Large-scale Lexicalized Case Frames | 45 |
| 17 | 1 | |
| 18 | Japanese Named Entity Recognition Using Structural Natural Language Processing. | 35 |
| 19 | 3 | |
| 20 | Toward Text Understanding: Integrating Relevance-tagged Corpus and Automatically Constructed Case Frames | 3 |
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.