Yuto Yamaguchi
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- Tensor decomposition and applications 2
- Transportation top 10%
- Human Mobility and Location-Based Analysis 3
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- Complex Network Analysis Techniques 12
- Opinion Dynamics and Social Influence 3
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- Web Data Mining and Analysis 3
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- Advanced Text Analysis Techniques 2
- Text and Document Classification Technologies 2
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- Mobile Crowdsensing and Crowdsourcing 2
- Co-authors
- Hiroyuki KitagawaChristos FaloutsosToshiyuki AmagasaCaetano TrainaAlceu Ferraz CostaAgma J. M. TrainaKohei HayashiKazuhiro Sugamoto
- Journals
- International Journal of Molecular Sciences (1 paper)Lipids in Health and Disease (1 paper)ACM Transactions on Knowledge Discovery from Data (1 paper)
- Partner nations
- JapanUnited StatesBrazil
In The Last Decade
Yuto Yamaguchi
18 papers receiving 198 citations
Peers
Comparison fields: 5 of 56
- Computational Mathematics 5
- Transportation 47
- Statistical and Nonlinear Physics 78
- Geography, Planning and Development 21
- Signal Processing 40
Countries citing papers authored by Yuto Yamaguchi
This map shows the geographic impact of Yuto Yamaguchi'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 Yuto Yamaguchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuto Yamaguchi more than expected).
Fields of papers citing papers by Yuto Yamaguchi
This network shows the impact of papers produced by Yuto Yamaguchi. 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 Yuto Yamaguchi. The network helps show where Yuto Yamaguchi may publish in the future.
Co-authorship network
The 20 scholars most cited alongside Yuto Yamaguchi, 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 | 2023 | 2 | |
| 2 | 2022 | 3 | |
| 3 | 2021 | 1 | |
| 4 | 2021 | 0 | |
| 5 | 2018 | 8 | |
| 6 | 2018 | 4 | |
| 7 | 2017 | 6 | |
| 8 | 2017 | 15 | |
| 9 | 2017 | 5 | |
| 10 | 2017 | 1 | |
| 11 | 2016 | 17 | |
| 12 | 2016 | 4 | |
| 13 | 2015 | 1 | |
| 14 | 2015 | 57 | |
| 15 | 2015 | 16 | |
| 16 | 2014 | 23 | |
| 17 | 2013 | 19 | |
| 18 | 2012 | 3 | |
| 19 | 2011 | 22 |
About Yuto Yamaguchi
Yuto Yamaguchi is a scholar working on Computational Mathematics, Statistical and Nonlinear Physics and Transportation, having authored 19 papers that have together received 207 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (12 papers), Human Mobility and Location-Based Analysis (3 papers), Web Data Mining and Analysis (3 papers), Opinion Dynamics and Social Influence (3 papers), Advanced Text Analysis Techniques (2 papers), Mobile Crowdsensing and Crowdsourcing (2 papers), Tensor decomposition and applications (2 papers) and Text and Document Classification Technologies (2 papers). The work is most often cited by research in Computational Mathematics (5 citations), Transportation (47 citations) and Statistical and Nonlinear Physics (78 citations). Yuto Yamaguchi has collaborated with scholars based in Japan, United States and Brazil. Frequent co-authors include Hiroyuki Kitagawa, Christos Faloutsos, Toshiyuki Amagasa, Caetano Traina, Alceu Ferraz Costa, Agma J. M. Traina, Kohei Hayashi, Kazuhiro Sugamoto, Hiroaki Shiokawa and Mitsuo Yoshida. Their work appears in journals such as International Journal of Molecular Sciences, Lipids in Health and Disease and ACM Transactions on Knowledge Discovery from Data.
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.