• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to previous page

Development of statistical models for knowledge acquisition from large-scale data including multiform samples

Research Project

Project/Area Number 13680507
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field 社会システム工学
Research InstitutionGunma University

Principal Investigator

SEKI Yoichi  Gunma University, Department of Engineering, Professor, 工学部, 教授 (90196949)

Project Period (FY) 2001 – 2003
Project Status Completed (Fiscal Year 2003)
Budget Amount *help
¥3,100,000 (Direct Cost: ¥3,100,000)
Fiscal Year 2003: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 2002: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2001: ¥1,900,000 (Direct Cost: ¥1,900,000)
Keywordsdata mining / tree regression analysis / nonparametric regression / minimum description length / nearest neighborhood / POS data with customer ID / SOM / Nearest Neighbor / 交互作用効果 / POSデータ
Research Abstract

As theoretical viewpoints, we proposed the following models and developed the prototype programs of these methods with the statistical language S.
(1)We proposed a recursive partitioning linear model, which can be transformed to ordinal linear models, based on tree regression model with linear terms (Seki & Tsutsui 98).
(2)We proposed a process monitoring chart to monitor the parts whether irregular deterioration occurred, supposing that the deterioration characteristic can be continuously monitored by development of sensor technology.
(3)We proposed a method to estimate a Nearest Neighbor type non-parametric regression model, by optimizing the weight of the weighted Euclidian distance, in order to take into consideration the levels of explanation variables effect.
(4)We proposed a method which stratifies sample set by discriminating the class in which the relation between the response variable and explanation variables are similar, in the case where two explanation variable sets are given : one can be used for stratification of sample set, and another can be used for regression of response variable.
(5)We proposed a non-parametric, test using Minimum Description length criterion for comparing dose levels. In order to verify proposed methodology about POS (Point Of Sales) data with customer ID, we participate in the data analysis competition sponsored by the Operations Research Society of Japan etc., and obtained the following results.
2001 a food supermarket's data, competition championship
2002 a department store's data, Sectional-meeting fighting spirit award
2003 3 department stores' data, Sectional-meeting superior prize

Report

(4 results)
  • 2003 Annual Research Report   Final Research Report Summary
  • 2002 Annual Research Report
  • 2001 Annual Research Report
  • Research Products

    (14 results)

All Other

All Publications (14 results)

  • [Publications] 星野 直人, 関 庸一: "MDL基準による用量水準比較のためのノンパラメトリック検定"計算機統計学. 14・1. 45-55 (2001)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2003 Final Research Report Summary
  • [Publications] 関 庸一, 下田祐紀夫, エルニ ドゥイ スマヤティ: "混合効果モデルによる異常劣化モニタリング法"品質. 32・4. 100-110 (2002)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2003 Final Research Report Summary
  • [Publications] 関 庸一: "ID付きPOSデータからの顧客行動パタンの抽出"オペレーションズ・リサーチ. 48・2. 75-82 (2003)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2003 Final Research Report Summary
  • [Publications] 関 庸一, 小茂田 宏, 石原 淳一郎: "事象系列のストリング分析-百貨店における買回り行動の分析"オペレーションズ・リサーチ. 49・2. 67-82 (2004)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2003 Final Research Report Summary
  • [Publications] 関 庸一, 野島 勇: "交互作用効果による再帰分割線形モデル"応用統計学. 33(印刷中). (2004)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2003 Final Research Report Summary
  • [Publications] Naoto Koshino, Yoichi Seki: "A Nonparametric test based on the MDL Criterion for Comparing Dose Levels"Bulletin of the Computational Statistics of Japan. Vol.14, No.1. 45-55 (2001)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2003 Final Research Report Summary
  • [Publications] Yoichi Seki, Yukio Shimoda, Erni Dwi Sumaryatie: "Monitoring Method for Detection of Irregular Deterioration using Mixed Effect Model"Journal of the Japanese Society for Quality Control. Vol.32, No.4. 100-110 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2003 Final Research Report Summary
  • [Publications] Yoichi Seki: "A Method to extract customer behavior patterns from POS data including customer ID"Communication of the Operations Research Society of Japan. Vol.48, No.2. 75-82 (2003)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2003 Final Research Report Summary
  • [Publications] Yoichi Seki, Hiroshi Komoda, Jun'ichiro Ishihara: "String Analysis of event series -Analysis of shopping in a department store"Communication of the Operations Research Society of Japan. Vol.49, No.2. 67-74 (2004)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2003 Final Research Report Summary
  • [Publications] Seki Yoichi, Nojima Isamu: "Recursive partitioning linear model using interaction effect criterion"Japanese Journal of Applied Statistics. (in printing). (2004)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2003 Final Research Report Summary
  • [Publications] 関 庸一, 小茂田 宏, 石原 淳一郎: "事象系列のストリング分析 -百貨店における買回り行動の分析"オペレーションズ・リサーチ. 49・2. 67-82 (2004)

    • Related Report
      2003 Annual Research Report
  • [Publications] 関 庸一, 下田祐紀夫, エルニ ドゥイ スマヤティ: "混合効果モデルによる異常劣化モニタリング法"品質,2002,100-110. 32・4. 100-110 (2002)

    • Related Report
      2002 Annual Research Report
  • [Publications] 関 庸一: "ID付きPOSデータからの顧客行動パタンの抽出"オペレーションズ・リサーチ. 48・2. 75-82 (2003)

    • Related Report
      2002 Annual Research Report
  • [Publications] 星野 直人, 関 庸一: "MDL基準による用量水準比較のためのノンパラメトリック検定"計算機統計学. 14・1. 45-55 (2001)

    • Related Report
      2002 Annual Research Report

URL: 

Published: 2001-04-01   Modified: 2016-04-21  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi