{"id":223527,"updated":"2025-01-19T13:18:41.944306+00:00","links":{},"created":"2025-01-19T01:23:23.190917+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00223527","sets":["581:11107:11108"]},"path":["11108"],"owner":"44499","recid":"223527","title":["スマートフォンログに基づくwell-being指標と下位尺度の推定"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-01-15"},"_buckets":{"deposit":"e28ac4eb-c54e-45c5-84e6-95d9cda85859"},"_deposit":{"id":"223527","pid":{"type":"depid","value":"223527","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"スマートフォンログに基づくwell-being指標と下位尺度の推定","author_link":["588839","588830","588834","588845","588833","588827","588835","588831","588828","588836","588840","588841","588842","588844","588832","588829","588838","588843","588837","588846"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"スマートフォンログに基づくwell-being指標と下位尺度の推定"},{"subitem_title":"Estimating Subjective Well-being Scale and Subscales Using Smartphone Logs","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[特集:新社会とスマートコミュニティ創成に向けたモバイルコンピューティングと高度交通システム] スマートフォン，ヘルスケア，well-being，クラスタリング，機械学習","subitem_subject_scheme":"Other"}]},"item_type_id":"2","publish_date":"2023-01-15","item_2_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":"東京大学"},{"subitem_text_value":"東京大学"},{"subitem_text_value":"東京大学"},{"subitem_text_value":"慶應義塾大学"},{"subitem_text_value":"慶應義塾大学"},{"subitem_text_value":"慶應義塾大学"}]},"item_2_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":"The University of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"The University of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"The University of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"Keio University","subitem_text_language":"en"},{"subitem_text_value":"Keio University","subitem_text_language":"en"},{"subitem_text_value":"Keio University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing 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尚志"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山本, 直樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"荒川, 大輝"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"檜山, 聡"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"姚, 文昊"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"上西, 康平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"太田, 順"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"寺澤, 悠理"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"沖村, 宰"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"前田, 貴記"}],"nameIdentifiers":[{}]}]},"item_2_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Takashi, Hamatani","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Naoki, Yamamoto","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hiroki, Arakawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Satoshi, Hiyama","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Wenhao, Yao","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kohei, Kaminishi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Jun, Ota","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yuri, Terasawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tsukasa, Okimura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takaki, Maeda","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_2_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00116647","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_2_publisher_15":{"attribute_name":"公開者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"item_2_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7764","subitem_source_identifier_type":"ISSN"}]},"item_2_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年スマートフォンの普及が進んでおり，スマートフォンを用いたヘルスケア技術に期待が高まってきている．スマートフォンは日々ユーザが持ち歩き，使われるものであるため，well-being（身体・精神・社会的に健康で幸福である状態）などユーザの心理状態を反映することが期待できる．本研究では，スマートフォンに搭載されるセンサや利用履歴より得られる情報に基づき得られる行動特徴量をもとに，利用者のwell-beingを推定する．さらに，スマートフォンから得られる行動特徴量の異なる側面に着目することで，well-beingの総合的な指標だけでなく，well-beingを構成する要素（身体的健康や家族とのつながりなど）を推定する．実際に90人から321サンプルを収集し，クラスタリングにより特徴量の傾向が類似するユーザ群を集めて推定モデルを構築し評価を行った結果，全体のwell-being申告値が低下するかどうかの2クラス分類問題においてF値=0.907，7種類の下位尺度について平均F値0.682-0.874の範囲でそれぞれ推定でき，クラスタごとに異なる種類の特徴量を利用することでより高い推定精度が得られることを明らかにした．","subitem_description_type":"Other"}]},"item_2_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"The recent spread of smartphones derives growing interest in its application in health and medical care domains. Smartphone has the potential to reflect their owner's psychological states in sensor log and usage history. In this study, we propose a method to estimate the change in users' subjective well-being scales and those subcomponents using smartphone logs. For the precise estimation of well-being scales, the clustering algorithm is applied to separate similar user groups. The evaluation result revealed that binary classification accuracy (F1 score) was 0.899 by using a clustering algorithm and the change of seven subcomponents of the well-being scale was estimated between 0.682 and 0.874.","subitem_description_type":"Other"}]},"item_2_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"144","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌"}],"bibliographicPageStart":"134","bibliographicIssueDates":{"bibliographicIssueDate":"2023-01-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"64"}]},"relation_version_is_last":true,"item_2_identifier_registration":{"attribute_name":"ID登録","attribute_value_mlt":[{"subitem_identifier_reg_text":"10.20729/00223418","subitem_identifier_reg_type":"JaLC"}]},"weko_creator_id":"44499"}}