{"created":"2025-01-19T01:44:39.908606+00:00","updated":"2025-01-19T07:58:23.997039+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00240462","sets":["1164:3980:11478:11783"]},"path":["11783"],"owner":"44499","recid":"240462","title":["認知バイアスと大規模言語モデルを活用したメッセージ最適化システムの提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-10-29"},"_buckets":{"deposit":"55a8bf86-7a47-41a9-b98d-f63c346dfb51"},"_deposit":{"id":"240462","pid":{"type":"depid","value":"240462","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"認知バイアスと大規模言語モデルを活用したメッセージ最適化システムの提案","author_link":["659693","659691","659690","659689","659692"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"認知バイアスと大規模言語モデルを活用したメッセージ最適化システムの提案"},{"subitem_title":"Proposal of a message optimization system utilizing cognitive bias and large-scale language models","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"一般セッション2","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-10-29","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"株式会社NTTドコモ"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"NTT DOCOMO, inc.","subitem_text_language":"en"},{"subitem_text_value":"NTT DOCOMO, inc.","subitem_text_language":"en"},{"subitem_text_value":"NTT DOCOMO, inc.","subitem_text_language":"en"},{"subitem_text_value":"NTT DOCOMO, inc.","subitem_text_language":"en"},{"subitem_text_value":"NTT DOCOMO, inc.","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/240462/files/IPSJ-ITS24099016.pdf","label":"IPSJ-ITS24099016.pdf"},"date":[{"dateType":"Available","dateValue":"2026-10-29"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ITS24099016.pdf","filesize":[{"value":"1.1 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":"37"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"c2921b49-29e1-479c-bfb9-ad7c1d27b11a","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":"吉川, 裕木子"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"酒井, 亮勢"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鈴木, 明作"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鈴木, 喬"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"石川, 太朗"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11515904","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":"2188-8965","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"エコ行動促進アプリの利用率向上を目指し，大規模言語モデルによるメッセージ生成と，ユーザの認知バイアスに基づいたメッセージ最適化システムを提案する．従来の手法では，過去の当該サービスの開封履歴のみに基づいて最適化を行っており，過去の認知バイアスの種類やプッシュ通知の文言に依存した最適化となってしまう．その結果，最適化に用いられるバイアスの種類が限られ，本来の効果が発揮されにくいだけでなく，利用率向上の効果が持続しにくいという課題があった．そこで本研究では，他のサービスから開封履歴を取得し，使用する認知バイアスの種類を増やす手法を提案する．さらに，効率的にプッシュ文言の内容を刷新するため，大規模言語モデルを活用した手法を組み込んだシステムを構築し，実際のサービスにおいてアプリの利用率向上に貢献できることを示した．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"To enhance the usage rate of an eco-friendly behavior promotion application, we propose a system that generates messages using a large language model and optimizes these messages based on users' cognitive biases. Traditional approaches optimize based on the history of opened notifications, relying on the types of cognitive biases and the wording of previous push messages. Consequently, the variety of biases used for optimization is limited, leading to reduced effectiveness and short-lived improvements in engagement rates. To address this issue, our study proposes methods to obtain open history data from other services, thereby increasing the types of cognitive biases employed. Additionally, we integrate a large language model to efficiently refresh the content of push messages. This system demonstrates its ability to contribute to the improvement of app usage rates in actual service scenarios.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告高度交通システムとスマートコミュニティ（ITS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-10-29","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"16","bibliographicVolumeNumber":"2024-ITS-99"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":240462,"links":{}}