{"created":"2025-01-19T01:29:03.050686+00:00","updated":"2025-01-19T11:26:46.807680+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229722","sets":["6504:11436:11438"]},"path":["11438"],"owner":"44499","recid":"229722","title":["最適化手法を用いた事例・変数統合型の欠損値補完"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"2a044c84-7546-4d96-b743-eda74f87e35f"},"_deposit":{"id":"229722","pid":{"type":"depid","value":"229722","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"最適化手法を用いた事例・変数統合型の欠損値補完","author_link":["617927","617926"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"最適化手法を用いた事例・変数統合型の欠損値補完"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ソフトウェア科学・工学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2023-02-16","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"筑波大"},{"subitem_text_value":"筑波大"}]},"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/229722/files/IPSJ-Z85-5M-08.pdf","label":"IPSJ-Z85-5M-08.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-5M-08.pdf","filesize":[{"value":"285.1 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"f4313880-76fa-45e6-bee2-8877e4b32b2b","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"松本, 拓見"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"高野, 祐一"}],"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_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"多くの場面でデータ分析が行われているが，データセットには欠損値が含まれる場合が多い．一方で機械学習では完全なデータセットを前提とした手法が多く，欠損部分を適切に扱う必要がある．先行研究では最適化手法を用いて欠損値補完を行い，多くのデータセットで従来の手法よりも優れた性能を示したが，事例間の関連性のみを利用し，変数間の関連性は考慮されていない．一方で推薦システムでは，利用者間だけでなくアイテム間の類似性を用いて評価値を予測する手法が有用である．そこで本研究では，事例間と変数間の近傍を利用した欠損値補完の最適化手法を提案し，数値実験によって有効性を検証する．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"394","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"393","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":229722,"links":{}}