{"created":"2025-01-19T01:44:27.399043+00:00","updated":"2025-01-19T08:00:50.855981+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00240327","sets":["6164:6165:6640:11802"]},"path":["11802"],"owner":"44499","recid":"240327","title":["GPTによる，ユーザのパーソナリティに焦点を当てたイベント推薦の評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-06-19"},"_buckets":{"deposit":"17f6574e-d3b9-46a0-b3ba-94c8f2ef14bb"},"_deposit":{"id":"240327","pid":{"type":"depid","value":"240327","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"GPTによる，ユーザのパーソナリティに焦点を当てたイベント推薦の評価","author_link":["659106","659108","659107"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"GPTによる，ユーザのパーソナリティに焦点を当てたイベント推薦の評価"},{"subitem_title":"Evaluation of Event Recommendation Focusing on User’s Personality by GPT","subitem_title_language":"en"}]},"item_type_id":"18","publish_date":"2024-06-19","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"お茶の水女子大学"},{"subitem_text_value":"日本アイ・ビー・エム"},{"subitem_text_value":"お茶の水女子大学"}]},"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/240327/files/IPSJ-DICOMO2024203.pdf","label":"IPSJ-DICOMO2024203.pdf"},"date":[{"dateType":"Available","dateValue":"2026-06-19"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2024203.pdf","filesize":[{"value":"2.3 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":"44"}],"accessrole":"open_date","version_id":"8a23f5c9-c8a3-44b0-bfe5-80e400d5a415","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"大本, 詩織"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"榎, 美紀"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小口, 正人"}],"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_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，イベント推薦システムが多く提案されており，ユーザの過去の訪問履歴や趣味趣向に焦点を当てたものから，性格特性に焦点を当てたものまで，様々なアプローチが存在する．しかし，既存の研究では，システムの構築をするにあたり多くの労力を要したり，学習コストが高いなどの理由から，様々な要因を組み合わせ，ユーザの状況に応じて柔軟にイベント推薦することが難しい．そこで，本研究では，GPTへのプロンプトを工夫することで，天気や日付といった情報や，ユーザの感情，趣味趣向，性格特性などを柔軟に組み合わせ，ユーザのその時の状況や気分に応じたイベント推薦を行うシステムの構築を提案する．本稿では，それぞれのユーザに柔軟に対応し，また容易に拡張することができるシステムの構築を目指し，一連の流れをすべて LLM によって行うことができるか検証を行なった．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"1520","bibliographic_titles":[{"bibliographic_title":"マルチメディア，分散，協調とモバイルシンポジウム2024論文集"}],"bibliographicPageStart":"1514","bibliographicIssueDates":{"bibliographicIssueDate":"2024-06-19","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":240327,"links":{}}