Information extraction and its interactive system for large-scale mixed and complex data

• Project/Area Number: 17K00063
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Statistical science
• Research Institution: Okayama University of Science
• Principal Investigator: Mori Yuichi 岡山理科大学, 経営学部, 教授 (80230085)
• Co-Investigator(Kenkyū-buntansha): 黒田 正博 岡山理科大学, 経営学部, 教授 (90279042) ; 飯塚 誠也 岡山大学, 全学教育・学生支援機構, 教授 (60322236) ; 久保田 貴文 多摩大学, 経営情報学部, 准教授 (30379705)
• Project Period (FY): 2017-04-01 – 2021-03-31
• Project Status: Completed (Fiscal Year 2020)
• Budget Amount: ¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000); Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000); Fiscal Year 2018: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000); Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
• Keywords: クラスタリング / 次元縮約 / 非計量多変量解析 / 数量化 / 計算効率 / 加速化アルゴリズム / 統計計算 / コンピュータ支援統計

Outline of Final Research Achievements

For mixed measurement levels and complexity in data, we proposed methods to extract the latent structures and features in the data, and to efficiently obtain the computational results, using simultaneous estimation of information reduction and clustering and variable selection. The methods enable us to deal with qualitative data in reduced k-means clustering and partial least squares method, to select a reasonable subset in non-linear principal component analysis, and to obtain the results quickly in non-linear principal component analysis, non-linear factor analysis and fuzzy c-means clustering.

Academic Significance and Societal Importance of the Research Achievements

一般的なデータサイズや質的データに特化された既存の手法に対して，尺度の統一的な扱いを適用し，大規模性を次元縮約と変数選択により軽減させ，情報縮約と分類の同時推定により，対象の考察のための有用な情報を得ようとしたところに，学術的な特色がある。また，数値解析の分野で提案されている加速化法を取り入れ，計算時間の面からも大規模性を克服しようとしたところに独創性がある。これらの手法により，これまでの手法では観察しづらかった知見が手早く得られるようになり，マーケティング分野やデータマイニングの適用場面で強力なツールになりうる点に社会的な意義が見出せる。

Research Products

• [Journal Article] 部分的最小二乗法における質的データの扱い (2021)
  • Author(s): 西山ちとせ，片山浩子，森 裕一
  • Journal Title: 経営とデータサイエンス Volume: 3 Pages: 26-33
  • Open Access
• [Journal Article] Initial Value Selection for the Alternating Least Squares Algorithm (2020)
  • Author(s): Masahiro Kuroda, Yuichi Mori, Masaya Iizuka
  • Journal Title: Advanced Studies in Classification and Data Science Volume: Chapter of Book Pages: 227-239
  • DOI: 10.1007/978-981-15-3311-2_18
  • ISBN: 9789811533105, 9789811533112
  • Peer Reviewed / Int'l Joint Research
• [Presentation] 尺度混在データに対する次元縮約とクラスタリング (2019)
  • Author(s): 森 裕一，吉岡嵩紹，片山浩子，黒田正博
  • Organizer: 2019年度統計関連学会連合大会
• [Presentation] Reduced K-Means with nonlinear principal component analysis (2019)
  • Author(s): Yoshioka, T., Kuroda, M., Mori, Y.
  • Organizer: The 62nd International Statistical Institute 2019 World Statistics Congress
  • Int'l Joint Research
• [Presentation] Some Applications in Multivariate Methods with Alternating Least Squares (2019)
  • Author(s): Mori, Y., Katayama, H., Yoshioka, T., Kuroda, M., Iizuka, M.
  • Organizer: Data Science, Statistics & Visualisation 2019
  • Int'l Joint Research
• [Presentation] vεアルゴリズムによるファジィc平均法の計算の加速化 (2018)
  • Author(s): 吉岡嵩紹，黒田正博，森 裕一
  • Organizer: 日本計算機統計学会第32回大会
• [Presentation] Speed-up of bootstrap computation of the covariance matrix of MLEs from incomplete data (2018)
  • Author(s): Kuorda, M., Mori, Y.
  • Organizer: The 2nd International Conference on Econometrics and Statistics
  • Int'l Joint Research
• [Presentation] Acceleration of computation for fuzzy c-means clustering (2018)
  • Author(s): Yoshioka, M., Kuroda, M., Mori, Y.
  • Organizer: The 23rd International Conference on Computational Statistics
  • Int'l Joint Research
• [Presentation] Speed-up of bootstrap computation to incomplete data (2018)
  • Author(s): Kuroda, M., Mori, Y.
  • Organizer: IASC-ARS 25th Anniversary Conference & CASC 2nd Annual Conference
  • Int'l Joint Research
• [Presentation] Computational efficiency for fuzzy clustering (2018)
  • Author(s): Yoshioka, M., Kuroda, M., Mori, Y.
  • Organizer: The 11th International Conference of the ERCIM WG on Computational and Methodological Statistics
  • Int'l Joint Research / Invited
• [Presentation] Variable selection for mixed measurement level data in dimension reduction methods and its computation (2017)
  • Author(s): Mori, Y., Iizuka, M., Kuorda, M.
  • Organizer: The 1st International Conference on Econometrics and Statistics (EcoSta 2017)
  • Int'l Joint Research
• [Presentation] Initial value selection for the alternating least squares algorithm (2017)
  • Author(s): Kuroda, M., Mori, Y., Iizuka, M.
  • Organizer: Conference of the International Federation of Classification Societies 2017
  • Int'l Joint Research
• [Presentation] Item selection for impression survey (2017)
  • Author(s): Katayama, H., Mori, Y.
  • Organizer: 2017 Hangzhou International Statistical Symposium
  • Int'l Joint Research
• [Presentation] Improvement of Computation for Nonlinear Multivariate Methods (2017)
  • Author(s): Kuroda, M., Mori, Y., Iizuka, M.
  • Organizer: The 10th Conference of the IASC-ARS/68th Annual NZSA Conference
  • Int'l Joint Research / Invited