{"updated":"2025-01-20T08:31:24.522527+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00170547","sets":["1164:5064:8574:8864"]},"path":["8864"],"owner":"11","recid":"170547","title":["作業用BGMに特化した楽曲推薦システム"],"pubdate":{"attribute_name":"公開日","attribute_value":"2016-07-23"},"_buckets":{"deposit":"2fe3cb80-8644-4507-afef-e88aa4ac233e"},"_deposit":{"id":"170547","pid":{"type":"depid","value":"170547","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"作業用BGMに特化した楽曲推薦システム","author_link":["344182","344180","344181"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"作業用BGMに特化した楽曲推薦システム"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"音楽分析","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2016-07-23","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"筑波大学情報学群情報科学類"},{"subitem_text_value":"産業技術総合研究所"},{"subitem_text_value":"産業技術総合研究所"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"College of Information Science, University of Tsukuba","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)","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/170547/files/IPSJ-MUS16112003.pdf","label":"IPSJ-MUS16112003.pdf"},"date":[{"dateType":"Available","dateValue":"2018-07-23"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MUS16112003.pdf","filesize":[{"value":"1.8 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":"21"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"b6e4c593-3add-4a75-8520-1d4d7f4dcce2","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2016 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"矢倉, 大夢"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中野, 倫靖"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"後藤, 真孝"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10438388","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":"2188-8752","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本稿では，作業時に集中度を高めることを目的として聴取する楽曲，「作業用 BGM」 に特化した楽曲推薦システムを提案する．従来，ユーザが好むであろう楽曲を推薦する手法が研究されてきたが，「とても好き」 な楽曲は作業者の集中を阻害することが知られており，作業用 BGM として推薦する楽曲に適していない．提案システムは，「とても好き」 や 「とても嫌い」 ではなく、「好き」 もしくは 「どちらともいえない」 楽曲を，BGM 聴取時のユーザからのフィードバックに基づいて推薦する．具体的には，楽曲のサビ区間までをダイジェスト的に聴取する （部分的にしか再生されない） システムとして設計することで，楽曲を 「スキップ」 するフィードバックによって 「嫌い」 な楽曲を推定する従来手法に加え，「もっと聴く」 フィードバックを導入して 「好き」 な楽曲を推定する．さらに，「好き」 として推定された楽曲は，ユーザの集中度を行動ログから推定して 「とても好き」 か 「好き」 かを識別する．これは集中度が高い時のフィードバックは，低い時より嗜好度を強く表しているという仮説に基づく．そして，楽曲間類似度に基づく Label Spreading により，頑健にかつ再生履歴が少ない状況でも適切に楽曲を推薦することを可能にした．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"10","bibliographic_titles":[{"bibliographic_title":"研究報告音楽情報科学（MUS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2016-07-23","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"3","bibliographicVolumeNumber":"2016-MUS-112"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"created":"2025-01-19T00:41:12.712158+00:00","id":170547,"links":{}}