{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00219578","sets":["6164:6165:6640:11008"]},"path":["11008"],"owner":"44499","recid":"219578","title":["日々の行動データを用いた時間割引率の推定"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-07-06"},"_buckets":{"deposit":"ec9fe91e-92e0-4fa4-bbb3-2c4278953c7f"},"_deposit":{"id":"219578","pid":{"type":"depid","value":"219578","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"日々の行動データを用いた時間割引率の推定","author_link":["572819","572821","572820","572822","572823"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"日々の行動データを用いた時間割引率の推定"}]},"item_type_id":"18","publish_date":"2022-07-06","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":"日本電信電話株式会社 NTT人間情報研究所"},{"subitem_text_value":"日本電信電話株式会社 NTT人間情報研究所"},{"subitem_text_value":"日本電信電話株式会社 NTT人間情報研究所"},{"subitem_text_value":"日本電信電話株式会社 NTT人間情報研究所"},{"subitem_text_value":"日本電信電話株式会社 NTT人間情報研究所"}]},"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/219578/files/IPSJ-DICOMO2022004.pdf","label":"IPSJ-DICOMO2022004.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-06"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2022004.pdf","filesize":[{"value":"2.0 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":"0fbbc436-330b-4787-ab80-29d115fe60d7","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"山本, 修平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"冨永, 登夢"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"倉島, 健"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"戸田, 浩之"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"西岡, 秀一"}],"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":"人間の性格を定量的に指標化することは，人間理解のための重要な取り組みの一つである．時間割引率は経済学の中で扱われる性格指標の一つであり，「待つことをどれだけ嫌がるか」という人間の性質に着目した指標である．時間割引率は肥満率，喫煙率といったネガティブな生活習慣と相関があることが知られており，個人の時間割引率を明らかにすることで，自身や他者が「待つこと」の我慢強さを定量的に理解でき，意思決定の効果的な介入支援も可能になると考えられる．本論文では，ウェアラブルデバイスで観測可能な日々の細かな行動に着目し，行動データを用いた時間割引率推定手法を提案する．行動データから，行動の生起時刻，行動間の遷移特徴，またそれらの差異に関する特徴を抽出し，時間割引率との相関分析によって有効な特徴を獲得することで重回帰モデルを構築する．評価実験では，深層学習をベースとした多量の学習パラメータを要するモデルに比べ，適行動特徴を用いた提案手法が時間割引率を高精度に推定できることを示した．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"27","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2022論文集"}],"bibliographicPageStart":"17","bibliographicIssueDates":{"bibliographicIssueDate":"2022-07-06","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2022"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":219578,"updated":"2025-01-19T14:50:42.341030+00:00","links":{},"created":"2025-01-19T01:19:39.000809+00:00"}