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        <identifier>oai:ipsj.ixsq.nii.ac.jp:00182360</identifier>
        <datestamp>2025-01-20T04:06:26Z</datestamp>
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          <dc:title>情報損失指標の非数値データへの適用</dc:title>
          <dc:title xml:lang="en">Application of an Information Loss Index to Non-numerical Data</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>秋山, 寛子</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName>和田, 昌昭</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Hiroko, Akiyama</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Masaaki, Wada</jpcoar:creatorName>
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          <datacite:description descriptionType="Other">ミクロアグリゲーションにより失われる情報の量の割合を表す指標として，情報損失指標 ILD を定義する．ILD は，データ間の距離に基づき定義されるので，数値データだけでなく，適切な距離を選べば文字列で表現されるようなデータに対しても適用可能である．本論文では，ILD を非数値データセットに適用し，距離の設定について考察を行った．数値データセットに対するミクロアグリゲーションにおいてグループの代表値として平均値を用いる場合には，ILD は平均とデータの差の 2 乗和に基づいた情報損失指標と一致し，この情報損失指標を自然に拡張したものとなっている．</datacite:description>
          <datacite:description descriptionType="Other">We define a new information loss index ILD as the ratio of the amount of information lost by microaggregation. Since ILD is based on distance between data, it is applicable not only to numerical data, but also to data like ones represented by character strings if we choose suitable distance. In this paper, we apply ILD to non-numerical datasets, and discuss choice of distance. For microaggregation of numerical datasets using the average values as the representatives of groups, ILD coincides with the information loss index based on the sum of squares of the difference between the average and data. In this sense, ILD is a natural extension of the information loss index.</datacite:description>
          <dc:publisher xml:lang="ja">情報処理学会</dc:publisher>
          <datacite:date dateType="Issued">2017-06-16</datacite:date>
          <dc:language>jpn</dc:language>
          <dc:type rdf:resource="http://purl.org/coar/resource_type/c_18gh">technical report</dc:type>
          <jpcoar:identifier identifierType="URI">https://ipsj.ixsq.nii.ac.jp/records/182360</jpcoar:identifier>
          <jpcoar:sourceIdentifier identifierType="ISSN">2188-8833</jpcoar:sourceIdentifier>
          <jpcoar:sourceIdentifier identifierType="NCID">AN10505667</jpcoar:sourceIdentifier>
          <jpcoar:sourceTitle>研究報告数理モデル化と問題解決（MPS）</jpcoar:sourceTitle>
          <jpcoar:volume>2017-MPS-113</jpcoar:volume>
          <jpcoar:issue>10</jpcoar:issue>
          <jpcoar:pageStart>1</jpcoar:pageStart>
          <jpcoar:pageEnd>5</jpcoar:pageEnd>
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            <datacite:date dateType="Available">2019-06-16</datacite:date>
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