Satoshi Oyama
About
In The Last Decade
Satoshi Oyama
73 papers receiving 694 citations
Peers
Comparison fields: 5 of 104
- Artificial Intelligence 435
- Information Systems 211
- Computer Vision and Pattern Recognition 117
- Computer Science Applications 85
- Statistical and Nonlinear Physics 74
Countries citing papers authored by Satoshi Oyama
This map shows the geographic impact of Satoshi Oyama'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 Satoshi Oyama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Satoshi Oyama more than expected).
Fields of papers citing papers by Satoshi Oyama
This network shows the impact of papers produced by Satoshi Oyama. 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 Satoshi Oyama. The network helps show where Satoshi Oyama may publish in the future.
Co-authorship network of co-authors of Satoshi Oyama
This figure shows the co-authorship network connecting the top 25 collaborators of Satoshi Oyama. A scholar is included among the top collaborators of Satoshi Oyama 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 Satoshi Oyama. Satoshi Oyama 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 | 1 | |
| 4 | 105 | |
| 5 | Evaluation of causal discovery models in bivariate case using real world data | 1 |
| 6 | Crowdsourced semantic matching of multi-label annotations | 6 |
| 7 | Automated Test Generation for Object-Oriented Programs with Multiple Targets | 2 |
| 8 | Accurate integration of crowdsourced labels using workers' self-reported confidence scores | 33 |
| 9 | 2 | |
| 10 | 43 | |
| 11 | Learning a Robust Relevance Model for Search Using Kernel Methods | 5 |
| 12 | 21 | |
| 13 | Evaluation of Reputations in CGM based on Identification of Reviewer's Activity Area | 0 |
| 14 | Extracting Conceptural Hierarchies from the Web by Term Coordinate and Property Inheritance Relationships | 0 |
| 15 | 1 | |
| 16 | Web Search Personalization based on Semantic Relationships between Terms Extracted from Personal Documents | 3 |
| 17 | Exploiting Document Structures for Comparing and Exploring Topics on the Web. | 7 |
| 18 | 1 | |
| 19 | 0 | |
| 20 | Keyword spices: a new method for building domain-specific web search engines | 17 |
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.