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

An approach to symbolic data analysis based on the quantile method

Research Project

Project/Area Number 22500138
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field Intelligent informatics
Research InstitutionTokyo Denki University

Principal Investigator

ICHINO Manabu  東京電機大学, 理工学部, 教授 (40057245)

Project Period (FY) 2010 – 2012
Project Status Completed (Fiscal Year 2012)
Budget Amount *help
¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2012: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2011: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2010: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Keywordsシンボリック・データ・アナリシス / データマイニング / 分位数 / 数量化 / 多変量解析 / 主成分分析 / 単調性 / 分布関数 / 概念クラスタリング / データ累積 / 年次データの解析 / 教師付き概念クラスタリング / 入れ子構造 / 順位相関 / スピアマン
Research Abstract

Symbolic data analysis aims to analyze complex data table described by the mixture of histograms, intervals, finite sets, and others. We usually obtain symbolic data tables by the process of aggregation and summarization of vastly many data sets. We assume proper cumulative distribution functions for feature values of histograms, intervals, finite sets, and others. Then. We can obtain the respective (m+1) vectors of quantile values. A main contribution to this study is the realization of the quantile method of principal component analysis for symbolic data tables. The quantile method transforms the given (N objects) ×(d features) symbolic data table to a standard numerical data table of the size (N×(m+1) sub-objects)×(d features) for a preselected integer number m which controls the representation quality for each symbolic object. We apply the standard principal component analysis to the transformed data table. In the obtained factor planes, each symbolic object is reproduced as a series of m connected arrow lines that combine (m+1) sub-objects. We reported the usefulness of the proposed method to the Journal of Statistical Analysis and Data Mining.

Report

(4 results)
  • 2012 Annual Research Report   Final Research Report ( PDF )
  • 2011 Annual Research Report
  • 2010 Annual Research Report
  • Research Products

    (19 results)

All 2012 2011 2010 Other

All Journal Article (4 results) (of which Peer Reviewed: 4 results) Presentation (11 results) Remarks (4 results)

  • [Journal Article] A generalized measure of covariant relations based on relative neighborhood relations2011

    • Author(s)
      A. Nagoya, Y. Ono, M. Ichino
    • Journal Title

      Far East Journal of Theoretical Statistics

      Volume: 37, 2 Pages: 125-143

    • Related Report
      2012 Final Research Report
    • Peer Reviewed
  • [Journal Article] 局所決定係数を用いた多次元データにおける共変性の評価について2011

    • Author(s)
      石川,市野
    • Journal Title

      電子情報通信学会論文誌A

      Volume: J94-A Pages: 372-382

    • Related Report
      2012 Final Research Report
    • Peer Reviewed
  • [Journal Article] The quantile method for symbolic principal component, analysis2011

    • Author(s)
      Manabu Ichino
    • Journal Title

      Statistical Analysis and Data Mining

      Volume: 4, 2 Pages: 184-198

    • Related Report
      2012 Final Research Report
    • Peer Reviewed
  • [Journal Article] A generalized measure of covariant relations based on relative neighborhood relations2011

    • Author(s)
      A.Nagoya, Y.Ono, M.Ichino
    • Journal Title

      Far East Journal of Theoretical Statistics

      Volume: Vol.37 No.2 Pages: 125-143

    • Related Report
      2011 Annual Research Report
    • Peer Reviewed
  • [Presentation] The data accumulation PCA to analyze periodically summarized multiple data tables2012

    • Author(s)
      M. Ichino, P. Brito
    • Organizer
      COMSTAT-2012
    • Place of Presentation
      Limassol, Cyprus
    • Related Report
      2012 Final Research Report
  • [Presentation] The data accumulation PCA to analyze periodically summarized multiple data tables.2012

    • Author(s)
      Manabu Ichino
    • Organizer
      COMSTAT 2012
    • Place of Presentation
      Limassol, Cyprus
    • Related Report
      2012 Annual Research Report
  • [Presentation] The data accumulation method for symbolic principal component analysis2011

    • Author(s)
      M. Ichino, P. Brito
    • Organizer
      ISI 2011
    • Place of Presentation
      Dublin, Ireland
    • Related Report
      2012 Final Research Report
  • [Presentation] Clustering symbolic data based on quantile representation2011

    • Author(s)
      P.Brito, M.Ichino
    • Organizer
      Workshop in Symbolic Data Analysis
    • Place of Presentation
      Namur, Belgium
    • Related Report
      2011 Annual Research Report
  • [Presentation] The data accumulation method for symbolic principal component analysis2011

    • Author(s)
      M.Ichino, P.Brito
    • Organizer
      ISI2011
    • Place of Presentation
      Dublin, Ireland
    • Related Report
      2011 Annual Research Report
  • [Presentation] Conceptual clustering of symbolic data using a quantile representation2011

    • Author(s)
      P.Brito, M.Ichino
    • Organizer
      Workshop on Theory and Application of High-dimensional Complex and Symbolic Data Analysis in Economics and Management Science
    • Place of Presentation
      Beijing, China
    • Related Report
      2011 Annual Research Report
  • [Presentation] Conceptual clustering of symbolic data using quantile representations approaches2011

    • Author(s)
      P.Brito, M.Ichino
    • Organizer
      4th International Conference of the ERCIM WG on Computing & Statistics
    • Place of Presentation
      London, England
    • Related Report
      2011 Annual Research Report
  • [Presentation] Symbolic clustering based on quantile representation2010

    • Author(s)
      P. Brito, M. Ichino
    • Organizer
      COMSTAT 2010 (19^<th> International Conference on Computational Statistics)
    • Place of Presentation
      Paris, France
    • Related Report
      2012 Final Research Report
  • [Presentation] The quantile method for symbolic hierarchical clustering2010

    • Author(s)
      M. Ichino, P. Brito
    • Organizer
      GfKl 2010 Symposium Karsruhe
    • Place of Presentation
      Karlsruhe, Germany
    • Related Report
      2012 Final Research Report
  • [Presentation] The quantile method for symbolic hierarchical clustering2010

    • Author(s)
      M.Ichino
    • Organizer
      GfKI 2010 Symposium
    • Place of Presentation
      Karlsruhe, Germany
    • Related Report
      2010 Annual Research Report
  • [Presentation] Symbolic clustering based on quantile representation2010

    • Author(s)
      P.Brito
    • Organizer
      COMPSTAT 2010
    • Place of Presentation
      Paris, France
    • Related Report
      2010 Annual Research Report
  • [Remarks] ホームページ

    • URL

      http://www.csm.ia.dendai.ac.jp

    • Related Report
      2012 Final Research Report
  • [Remarks] 市野研究室ホームページ

    • URL

      http://www.csm.ia.dendai.ac.jp

    • Related Report
      2012 Annual Research Report
  • [Remarks]

    • URL

      http://www.csm.ia.dendai.ac.jp

    • Related Report
      2011 Annual Research Report
  • [Remarks]

    • URL

      http://www.csm.ia.dendai.ac.jp

    • Related Report
      2010 Annual Research Report

URL: 

Published: 2010-08-23   Modified: 2019-07-29  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi