Masaki Uto

713 total citations
31 papers, 315 citations indexed

About

Masaki Uto is a scholar working on Artificial Intelligence, Management Science and Operations Research and Information Systems. According to data from OpenAlex, Masaki Uto has authored 31 papers receiving a total of 315 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 11 papers in Management Science and Operations Research and 7 papers in Information Systems. Recurrent topics in Masaki Uto's work include Topic Modeling (11 papers), Psychometric Methodologies and Testing (10 papers) and Natural Language Processing Techniques (5 papers). Masaki Uto is often cited by papers focused on Topic Modeling (11 papers), Psychometric Methodologies and Testing (10 papers) and Natural Language Processing Techniques (5 papers). Masaki Uto collaborates with scholars based in Japan and Italy. Masaki Uto's co-authors include Maomi Ueno, Yoshihiro Kato, Y. Tomikawa, Ayaka Suzuki, Koji Nakajima, Filippo Sciarrone, Marco Temperini, Minoru Nakayama and Hiroh Yamamoto and has published in prestigious journals such as PLoS ONE, Behavior Research Methods and Heliyon.

In The Last Decade

Masaki Uto

28 papers receiving 308 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Masaki Uto Japan 11 183 78 64 59 55 31 315
F. Jay Breyer United States 5 134 0.7× 66 0.8× 87 1.4× 32 0.5× 37 0.7× 10 272
Susanne Wolff United States 8 239 1.3× 106 1.4× 68 1.1× 27 0.5× 24 0.4× 13 372
Chi Lu United States 5 207 1.1× 88 1.1× 45 0.7× 26 0.4× 15 0.3× 10 271
Elissavet Georgiadou Greece 9 74 0.4× 128 1.6× 97 1.5× 142 2.4× 44 0.8× 16 351
S. Hunka Canada 4 131 0.7× 47 0.6× 56 0.9× 33 0.6× 124 2.3× 13 317
Debora de Chiusole Italy 11 225 1.2× 60 0.8× 23 0.4× 56 0.9× 54 1.0× 25 286
Semire Dikli United States 5 209 1.1× 101 1.3× 249 3.9× 56 0.9× 12 0.2× 5 516
Deborah J. Harris United States 13 38 0.2× 31 0.4× 91 1.4× 18 0.3× 265 4.8× 41 430
Anthony F. Botelho United States 10 211 1.2× 45 0.6× 58 0.9× 195 3.3× 5 0.1× 29 314
Alexis Palmer Germany 14 417 2.3× 35 0.4× 26 0.4× 14 0.2× 9 0.2× 57 484

Countries citing papers authored by Masaki Uto

Since Specialization
Citations

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

Fields of papers citing papers by Masaki Uto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masaki Uto

This figure shows the co-authorship network connecting the top 25 collaborators of Masaki Uto. A scholar is included among the top collaborators of Masaki Uto 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 Masaki Uto. Masaki Uto 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
1.
Tomikawa, Y. & Masaki Uto. (2024). Difficulty-Controllable Reading Comprehension Question Generation Considering the Difficulty of Reading Passages. International Conference on Computers in Education. 2 indexed citations
2.
Tomikawa, Y., et al.. (2024). Enhancing Diversity in Difficulty-Controllable Question Generation for Reading Comprehension via Extended T5. International Conference on Computers in Education. 1 indexed citations
3.
Uto, Masaki, et al.. (2024). Linking essay-writing tests using many-facet models and neural automated essay scoring. Behavior Research Methods. 56(8). 8450–8479. 1 indexed citations
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Tomikawa, Y., Ayaka Suzuki, & Masaki Uto. (2024). Adaptive Question–Answer Generation With Difficulty Control Using Item Response Theory and Pretrained Transformer Models. IEEE Transactions on Learning Technologies. 17. 2186–2198. 2 indexed citations
7.
Uto, Masaki, Y. Tomikawa, & Ayaka Suzuki. (2023). Difficulty-Controllable Neural Question Generation for Reading Comprehension using Item Response Theory. 119–129. 2 indexed citations
8.
Uto, Masaki, et al.. (2023). Integration of Prediction Scores From Various Automated Essay Scoring Models Using Item Response Theory. IEEE Transactions on Learning Technologies. 16(6). 983–1000. 13 indexed citations
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Uto, Masaki. (2022). A Bayesian many-facet Rasch model with Markov modeling for rater severity drift. Behavior Research Methods. 55(7). 3910–3928. 9 indexed citations
11.
Nakayama, Minoru, Filippo Sciarrone, Marco Temperini, & Masaki Uto. (2022). Evaluation of Programming Skills via Peer Assessment and IRT Estimation Techniques. IRIS Research product catalog (Sapienza University of Rome). 1–8.
12.
Uto, Masaki, et al.. (2021). Learning Automated Essay Scoring Models Using Item-Response-Theory-Based Scores to Decrease Effects of Rater Biases. IEEE Transactions on Learning Technologies. 14(6). 763–776. 18 indexed citations
13.
Uto, Masaki. (2021). A review of deep-neural automated essay scoring models. Behaviormetrika. 48(2). 459–484. 48 indexed citations
14.
Uto, Masaki, et al.. (2020). Time- and Learner-Dependent Hidden Markov Model for Writing Process Analysis Using Keystroke Log Data. International Journal of Artificial Intelligence in Education. 30(2). 271–298. 3 indexed citations
15.
Uto, Masaki. (2020). Accuracy of performance-test linking based on a many-facet Rasch model. Behavior Research Methods. 53(4). 1440–1454. 13 indexed citations
16.
Uto, Masaki, et al.. (2020). Neural Automated Essay Scoring Incorporating Handcrafted Features. 6077–6088. 54 indexed citations
17.
Uto, Masaki & Maomi Ueno. (2018). Empirical comparison of item response theory models with rater's parameters. Heliyon. 4(5). e00622–e00622. 22 indexed citations
18.
Uto, Masaki, et al.. (2017). Social constructivist approach of motivation: social media messages recommendation system. Behaviormetrika. 8 indexed citations
19.
Uto, Masaki & Maomi Ueno. (2015). Academic Writing Support System Using Bayesian Networks. 385–387. 3 indexed citations
20.
Uto, Masaki & Maomi Ueno. (2011). Article Structure Construction Support System by Bayes Code. 94(12). 2069–2081. 1 indexed citations

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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