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Masaki Uto
Masaki Uto
Associate Professor,The University of Electro-communications
Verified email at ai.lab.uec.ac.jp - Homepage
Title
Cited by
Cited by
Year
Neural automated essay scoring incorporating handcrafted features
M Uto, Y Xie, M Ueno
Proceedings of the 28th International Conference on Computational …, 2020
912020
Item Response Theory for Peer Assessment
M Uto, M Ueno
IEEE Transactions on Learning Technologies, 2015
862015
A review of deep-neural automated essay scoring models
M Uto
Behaviormetrika 48 (2), 459-484, 2021
542021
Empirical comparison of item response theory models with rater's parameters
M Uto, M Ueno
Heliyon 4 (5), 2018
542018
Robust neural automated essay scoring using item response theory
M Uto, M Okano
Artificial Intelligence in Education: 21st International Conference, AIED …, 2020
462020
A generalized many-facet Rasch model and its Bayesian estimation using Hamiltonian Monte Carlo
M Uto, M Ueno
Behaviormetrika 47 (2), 469-496, 2020
422020
Social constructivist approach of motivation: social media messages recommendation system
S Louvigné, M Uto, Y Kato, T Ishii
Behaviormetrika 45, 133-155, 2018
302018
Automated short-answer grading using deep neural networks and item response theory
M Uto, Y Uchida
Artificial Intelligence in Education: 21st International Conference, AIED …, 2020
292020
Group optimization to maximize peer assessment accuracy using item response theory and integer programming
M Uto, DT Nguyen, M Ueno
IEEE Transactions on Learning Technologies 13 (1), 91-106, 2019
262019
Rater-effect IRT model integrating supervised LDA for accurate measurement of essay writing ability
M Uto
Artificial Intelligence in Education: 20th International Conference, AIED …, 2019
252019
Item response theory without restriction of equal interval scale for rater’s score
M Uto, M Ueno
Artificial Intelligence in Education: 19th International Conference, AIED …, 2018
242018
Learning Automated Essay Scoring Models Using Item Response Theory-Based Scores to Decrease Effects of Rater Biases
M Uto, M Okano
IEEE Transactions on Learning Technologies, 2022
232022
Accuracy of performance-test linking based on a many-facet Rasch model
M Uto
Behavior Research Methods 53 (4), 1440-1454, 2021
232021
Consistent learning Bayesian networks with thousands of variables
K Natori, M Uto, M Ueno
Advanced Methodologies for Bayesian Networks, 57-68, 2017
232017
Constraint-based learning Bayesian networks using Bayes factor
K Natori, M Uto, Y Nishiyama, S Kawano, M Ueno
Advanced Methodologies for Bayesian Networks: Second International Workshop …, 2015
222015
他者からの学びを誘発する e ポートフォリオ
植野真臣, 宇都雅輝
日本教育工学会論文誌 35 (3), 169-182, 2011
202011
A multidimensional generalized many-facet Rasch model for rubric-based performance assessment
M Uto
Behaviormetrika 48 (2), 425-457, 2021
192021
Diverse reports recommendation system based on latent Dirichlet allocation
M Uto, S Louvigné, Y Kato, T Ishii, Y Miyazawa
Behaviormetrika 44, 425-444, 2017
182017
パフォーマンス評価のための項目反応モデルの比較と展望
宇都雅輝, 植野真臣
日本テスト学会誌 12 (1), 55-75, 2016
182016
Reliable Peer Assessment for Team-project-based Learning using Item Response Theory
T Nguyen, M Uto, Y Abe, M Ueno
International Conference on Computers in Education (ICCE), 144-156, 2015
172015
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