Junichi Toyoda

810 total citations
73 papers, 478 citations indexed

About

Junichi Toyoda is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Control and Systems Engineering. According to data from OpenAlex, Junichi Toyoda has authored 73 papers receiving a total of 478 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 21 papers in Electrical and Electronic Engineering and 16 papers in Control and Systems Engineering. Recurrent topics in Junichi Toyoda's work include Innovative Teaching and Learning Methods (10 papers), Open Education and E-Learning (10 papers) and Power System Reliability and Maintenance (9 papers). Junichi Toyoda is often cited by papers focused on Innovative Teaching and Learning Methods (10 papers), Open Education and E-Learning (10 papers) and Power System Reliability and Maintenance (9 papers). Junichi Toyoda collaborates with scholars based in Japan, United States and France. Junichi Toyoda's co-authors include M. Mizumoto, Akihiro Kashihara, Tsukasa Hirashima, Toru Shimada, Noriyuki Matsuda, Katsutoshi Hirayama, Tatsuo Akema, Atsuhiko Chiba, Shinobu Hasegawa and Masaaki KIMURA and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Information Sciences and Journal of the ACM.

In The Last Decade

Junichi Toyoda

64 papers receiving 437 citations

Peers

Junichi Toyoda
Comparison fields: 5 of 76
  • Electrical and Electronic Engineering 205
  • Artificial Intelligence 183
  • Computational Theory and Mathematics 83
  • Control and Systems Engineering 77
  • Management Science and Operations Research 73
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Citations per field, relative to Junichi Toyoda
Junichi Toyoda · 1×
Citations per year, relative to Junichi Toyoda
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Countries citing papers authored by Junichi Toyoda

Since Specialization
Citations

This map shows the geographic impact of Junichi Toyoda'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 Junichi Toyoda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junichi Toyoda more than expected).

Fields of papers citing papers by Junichi Toyoda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Junichi Toyoda. 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 Junichi Toyoda. The network helps show where Junichi Toyoda may publish in the future.

Co-authorship network of co-authors of Junichi Toyoda

This figure shows the co-authorship network connecting the top 25 collaborators of Junichi Toyoda. A scholar is included among the top collaborators of Junichi Toyoda 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 Junichi Toyoda. Junichi Toyoda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 3
2 1
3
Context-sensitive filtering for the web
5
4
Goal-Aware Exploration Makes Learning in Hyperspace Constructive.
0
5
Visualizing knowledge structure for exploratory learning in hyperspace
3
6
Reflection Support for Learning in Hyperspace.
5
7
Toward Context-Sensitive Filtering on WWW.
1
8 3
9
An Indexing Framework for Adaptive Arrangement of Mechanics Problems for ITS
3
10 17
11 2
12 2
13 1
14 2
15 5
16
1
17 1
18 17
19 16
20 57

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.

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