{"created":"2025-01-19T01:11:57.735360+00:00","updated":"2025-01-19T18:02:03.848860+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00210758","sets":["6164:6165:6640:10580"]},"path":["10580"],"owner":"44499","recid":"210758","title":["頻度情報の付加による匿名化データの有用性向上技術の一考察"],"pubdate":{"attribute_name":"公開日","attribute_value":"2020-06-17"},"_buckets":{"deposit":"df5dc1e0-8979-41ba-a275-8286b100b32f"},"_deposit":{"id":"210758","pid":{"type":"depid","value":"210758","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"頻度情報の付加による匿名化データの有用性向上技術の一考察","author_link":["534291","534289","534290"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"頻度情報の付加による匿名化データの有用性向上技術の一考察"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"プライバシー保護","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2020-06-17","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"富士通研究所"},{"subitem_text_value":"富士通研究所"},{"subitem_text_value":"富士通研究所"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/210758/files/IPSJ-DICOMO2020045.pdf","label":"IPSJ-DICOMO2020045.pdf"},"date":[{"dateType":"Available","dateValue":"2022-06-17"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2020045.pdf","filesize":[{"value":"1.4 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"7ea354bf-0d53-4809-aa7a-598fdca88f8b","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2020 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"寺田, 剛陽"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山岡, 裕司"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"福岡, 尊"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"AI を活用した高精度の分析には多くのデータを要する．自組織のデータだけで充分な精度が得られない場合はオープンデータや他組織のデータの活用が考えられるが，これらのデータは個人情報漏洩の防止の観点から匿名化が施されている．匿名化はデータの情報量を減らしてしまうため AI での分析精度に影響する．本論文では，匿名化によるデータ劣化を抑制するため，匿名化前の統計情報を匿名化後のデータに付与する方式を提案し評価した．結果，ロジスティック回帰，線形サポートベクター分類器との相性がよい傾向がわかった．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"304","bibliographic_titles":[{"bibliographic_title":"マルチメディア，分散協調とモバイルシンポジウム2064論文集"}],"bibliographicPageStart":"298","bibliographicIssueDates":{"bibliographicIssueDate":"2020-06-17","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2020"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":210758,"links":{}}