Rchr
J-GLOBAL ID:202301020835726486   Update date: Jan. 30, 2024

Uchiyama Toshio

ウチヤマ トシオ | Uchiyama Toshio
Affiliation and department:
Job title: Professer
Research theme for competitive and other funds  (2):
  • 2018 - 2022 Establishment of a diversity analysis method for probabilistic latent semantic analysis solutions
  • 2014 - 2017 Improvement of Nonnegative Matrix Factorization method using competitive learning
Papers (32):
  • Toshio Uchiyama, Tsukasa Hokimoto. Analysis of Solution Diversity in Topic Models for Smart City Applications. Sustainable Smart Cities - A Vision for Tomorrow. 2023. 51-70
  • Toshio Uchiyama, Tsukasa Hokimoto. A Word Distribution Based Analysis of the Diverse Solutions at Topic Models. 2022. J105-D. 5. 405-415
  • Toshio Uchiyama, Tsukasa Hokimoto. Analysis and visualization of solution diversity about topic model. 2019. J102-D. 10. 698-707
  • Toshio Uchiyama. A method for analyzing solution diversity in topic models. 2018 5th International Conference on Business and Industrial Research (ICBIR). 2018. 29-34
  • Okamoto, Kazuya, Uchiyama, Toshio, Takemura, Tadamasa, Kume, Naoto, Kuroda, Tomohiro, Yoshihara, Hiroyuki. Automatic selection of diagnosis procedure combination codes based on partial treatment data relative to the number of hospitalization days. Eur J Biomed. 2018. 14. 1. 45-51
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