{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00232785","sets":["1164:2735:11468:11517"]},"path":["11517"],"owner":"44499","recid":"232785","title":["欠損データ下における家具の組み合わせを用いたユーザ趣向抽出"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-02-29"},"_buckets":{"deposit":"27bb8240-2c79-464c-92de-169b5ac6db37"},"_deposit":{"id":"232785","pid":{"type":"depid","value":"232785","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"欠損データ下における家具の組み合わせを用いたユーザ趣向抽出","author_link":["630959","630958"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"欠損データ下における家具の組み合わせを用いたユーザ趣向抽出"}]},"item_type_id":"4","publish_date":"2024-02-29","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"同志社大学理工学研究科"},{"subitem_text_value":"同志社大学理工学部"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Science and Engineering, Doshisha University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Science and Engineering, Doshisha University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/232785/files/IPSJ-MPS24147002.pdf","label":"IPSJ-MPS24147002.pdf"},"date":[{"dateType":"Available","dateValue":"2026-03-01"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS24147002.pdf","filesize":[{"value":"3.7 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":"17"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"a2f1c674-0e50-44fd-979f-1e53924106a1","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"菅原, 茂剛"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小野, 景子"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10505667","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8833","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"e-コマースサイトの普及に伴い，ユーザの選好に沿った商品推薦への需要が高まっている．特に，インテリアの分野では，ユーザの好む家具の特徴や雰囲気などを明確に言語化することが難しく，ユーザが選好するインテリアスタイルを推定することが難しい．また，家具同士の組み合わせ方でインテリアスタイルは変化するため，ユーザごとの選好する組み合わせを考慮する必要があるが，学習データには全ての家具が揃わず欠損が生じることが普通である．そこで本研究では，家具画像から経験により抽出した画像特徴量とディープ画像特徴量を組み合わせ，欠損家具を考慮した XGBoost によるユーザの選好する家具スタイル推薦手法を提案する．実験結果では，代表的なディープラーニング手法と比較し，提案する画像特徴量の組み合わせが有効であること，欠損データを含む場合も性能が高いことを示す．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告数理モデル化と問題解決（MPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-02-29","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2024-MPS-147"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":232785,"updated":"2025-01-19T10:19:21.280475+00:00","links":{},"created":"2025-01-19T01:33:51.110870+00:00"}