Sadaaki Miyamoto
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- Multi-Criteria Decision Making 29
- Artificial Intelligence top 1%
- Advanced Clustering Algorithms Research 69
- Fuzzy Logic and Control Systems 21
- Bayesian Methods and Mixture Models 10
- Signal Processing top 2%
- Data Management and Algorithms 33
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- Face and Expression Recognition 41
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- Rough Sets and Fuzzy Logic 32
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- Fuzzy Systems and Optimization 16
In The Last Decade
Sadaaki Miyamoto
136 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 130
- Management Science and Operations Research 398
- Artificial Intelligence 1.0k
- Signal Processing 301
- Computer Vision and Pattern Recognition 507
- Computational Theory and Mathematics 326
Countries citing papers authored by Sadaaki Miyamoto
This map shows the geographic impact of Sadaaki Miyamoto'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 Sadaaki Miyamoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sadaaki Miyamoto more than expected).
Fields of papers citing papers by Sadaaki Miyamoto
This network shows the impact of papers produced by Sadaaki Miyamoto. 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 Sadaaki Miyamoto. The network helps show where Sadaaki Miyamoto may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sadaaki Miyamoto, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 6 | |
| 2 | 2011 | 15 | |
| 3 | ON THE COMPARISON OF SOME FUZZY CLUSTERING METHODS FOR PRIVACY PRESERVING DATA MINING: TOWARDS THE DEVELOPMENT OF SPECIFIC INFORMATION LOSS MEASURES | 2009 | 3 |
| 4 | Operations for Real-Valued Bags and Bag Relations | 2009 | 3 |
| 5 | An Explicit Mapping for Kernel Data Analysis and Application to Text Analysis | 2009 | 10 |
| 6 | On Tolerant Fuzzy c-Means Clustering with L1-Regularization | 2009 | 2 |
| 7 | 2009 | 9 | |
| 8 | 2008 | 9 | |
| 9 | 2008 | 2 | |
| 10 | 2008 | 9 | |
| 11 | Rough Sets and Current Trends in Computing: 5th International Conference, RSCTC 2006, Kobe, Japan, November 6-8, 2006, Proceedings (Lecture Notes in Computer Science) | 2006 | 1 |
| 12 | 2006 | 0 | |
| 13 | On the consistency of a Fuzzy C-Means algorithm for multisets | 2005 | 2 |
| 14 | METHODS OF FUZZY C-MEANS AND POSSIBILISTIC CLUSTERING USING A QUADRATIC TERM | 2004 | 6 |
| 15 | 2003 | 33 | |
| 16 | Fuzzy c-Means Clustering Using Transformations into High Dimensional Spaces | 2002 | 6 |
| 17 | 1998 | 1 | |
| 18 | 1997 | 1 | |
| 19 | 1994 | 1 | |
| 20 | 1977 | 2 |
About Sadaaki Miyamoto
Sadaaki Miyamoto is a scholar working on Artificial Intelligence, Signal Processing and Management Science and Operations Research, having authored 154 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (69 papers), Face and Expression Recognition (41 papers), Data Management and Algorithms (33 papers), Rough Sets and Fuzzy Logic (32 papers), Multi-Criteria Decision Making (29 papers), Fuzzy Logic and Control Systems (21 papers), Fuzzy Systems and Optimization (16 papers) and Bayesian Methods and Mixture Models (10 papers). The work is most often cited by research in Management Science and Operations Research (398 citations), Artificial Intelligence (1.0k citations) and Signal Processing (301 citations). Sadaaki Miyamoto has collaborated with scholars based in Japan, Slovenia and Spain. Frequent co-authors include Masao Mukaidono, Yasunori Endo, Yukihiro Hamasuna, Hidetomo Ichihashi, Katsuhiro Honda, Zhiqiang Liu, Vicenç Torra, Kazuhisa Nakayama, Yasuo Narukawa and Yuchi Kanzawa. Their work appears in journals such as PLoS ONE, Fuzzy Sets and Systems and Ecological Modelling.
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.