{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00219889","sets":["1164:6390:10768:10977"]},"path":["10977"],"owner":"44499","recid":"219889","title":["動画配信サービスにおけるeXplainable AIを用いたレコメンドモデルの評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-08-29"},"_buckets":{"deposit":"5c19e9a1-2245-4ede-bc9e-1507c14389bc"},"_deposit":{"id":"219889","pid":{"type":"depid","value":"219889","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"動画配信サービスにおけるeXplainable AIを用いたレコメンドモデルの評価","author_link":["574126","574125","574122","574127","574123","574124"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"動画配信サービスにおけるeXplainable 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kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"47"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"2a60d700-ce3c-4344-b831-57268e245c90","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"明石, 航"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"相場, 邦宏"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"伊藤, 拓"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"加藤, 剛志"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"佐藤, 篤"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"太田, 賢"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12628327","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":"2188-8604","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"EC サイトや動画配信サービスにおいて,ユーザへコンテンツを推薦する様々なレコメンドシステムが活用されている.レコメンドシステムにおける課題のひとつとして,推薦理由が不明確なことによる信頼性やユーザ満足度の低下が挙げられ,その結果 EC サイトにおける購買意欲の低下,動画配信サービスにおける視聴作品数減少に繋がる.この課題を解決する方法として,説明可能な AI(XAI:eXplainable AI)をレコメンドシステムに応用することで推薦結果と共に推薦理由をユーザに提示する方法が考えられる.本稿では,XAI を用いたレコメンドモデルのひとつである Attentive Multitask Collaborative Filtering(AMCF)において,ユーザに最適な推薦理由やバリエーションに富んだ作品を提示できているか,実際の動画配信サービス視聴ログを用いてオフライン検証を行った.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告コンシューマ・デバイス&システム(CDS)"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-08-29","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"4","bibliographicVolumeNumber":"2022-CDS-35"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":219889,"updated":"2025-01-19T14:44:39.605341+00:00","links":{},"created":"2025-01-19T01:19:56.666937+00:00"}