{"links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00215184","sets":["6504:10735:10807"]},"path":["10807"],"owner":"44499","recid":"215184","title":["リッチクライアント-エッジサーバ間における分散機械学習の検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-03-04"},"_buckets":{"deposit":"f89067f0-2a6b-454a-a6d3-5f559cb2ed85"},"_deposit":{"id":"215184","pid":{"type":"depid","value":"215184","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"リッチクライアント-エッジサーバ間における分散機械学習の検討","author_link":["553930","553934","553932","553933","553931"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"リッチクライアント-エッジサーバ間における分散機械学習の検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ネットワーク","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2021-03-04","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"お茶の水女子大"},{"subitem_text_value":"東大"},{"subitem_text_value":"東大"},{"subitem_text_value":"工学院大"},{"subitem_text_value":"お茶の水女子大"}]},"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/215184/files/IPSJ-Z83-4U-03.pdf","label":"IPSJ-Z83-4U-03.pdf"},"date":[{"dateType":"Available","dateValue":"2021-12-29"}],"format":"application/pdf","filename":"IPSJ-Z83-4U-03.pdf","filesize":[{"value":"446.1 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"28424255-4898-4129-89e8-2a2f862334ae","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"高野, 紗輝"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中尾, 彰宏"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山本, 周"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山口, 実靖"}],"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_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年IoTデバイスが普及し, 低遅延やネットワークの負荷分散が可能といった利点を持つエッジコンピューティングに注目が集まっている. 現在行われているこの分野の研究では, デバイス側はセンシングと通信を行うだけの位置付けとなっているものが多い. 一方で, リッチクライアントを用いてデータの発生源であるデバイス側で処理を行うと, 通信にかかるコストの削減やプライバシの保護が可能といった点で優れたシステムを構築できると考えられている. 本稿ではより多くの仕事をIoTデバイスに任せる事を目標とし, デバイス上で機械学習を行い, その場で結果を利用できるようにすると同時に学習の続きをエッジサーバで行うシステムの検討を行う.","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"170","bibliographic_titles":[{"bibliographic_title":"第83回全国大会講演論文集"}],"bibliographicPageStart":"169","bibliographicIssueDates":{"bibliographicIssueDate":"2021-03-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T16:16:54.672946+00:00","created":"2025-01-19T01:15:57.681342+00:00","id":215184}