{"links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229572","sets":["6504:11436:11437"]},"path":["11437"],"owner":"44499","recid":"229572","title":["機械学習を用いたグラフアルゴリズムの実行時間予測に関する一検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"adb3bf91-f552-4258-b270-e76072f562a7"},"_deposit":{"id":"229572","pid":{"type":"depid","value":"229572","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"機械学習を用いたグラフアルゴリズムの実行時間予測に関する一検討","author_link":["617511","617512","617513","617510"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"機械学習を用いたグラフアルゴリズムの実行時間予測に関する一検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"コンピュータシステム","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2023-02-16","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":"東北大"},{"subitem_text_value":"東北大"},{"subitem_text_value":"東北大"},{"subitem_text_value":"東北大"}]},"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/229572/files/IPSJ-Z85-5J-08.pdf","label":"IPSJ-Z85-5J-08.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-5J-08.pdf","filesize":[{"value":"252.4 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"19ba69db-be32-4376-9a79-9afb0af96a25","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"深澤, 祐輔"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小松, 一彦"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"佐藤, 雅之"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小林, 広明"}],"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，オンラインショッピングにおける商品レコメンドといった，グラフデータを高速に処理しサービスを提供する需要が高まっている．しかしアルゴリズムの選択によっては実行に膨大な時間がかかるため，実行前にグラフデータに適したアルゴリズムを把握する必要がある．本発表では，グラフデータにおける重要な特徴量であるエッジ数とアルゴリズムの実行時間との相関の高さに着目し，グラフデータとアルゴリズムの特徴量を入力とした回帰モデルを用いることで，高い精度での実行時間予測を行う手法を提案する．提案手法によって実行時間の短いアルゴリズムの選択可能であることを明らかにする．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"80","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"79","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T11:30:26.551879+00:00","created":"2025-01-19T01:28:48.632522+00:00","id":229572}