{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00231641","sets":["1164:3027:11450:11451"]},"path":["11451"],"owner":"44499","recid":"231641","title":["固有表現アノテーションにおける画面操作記録を用いた不良回答検出"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-01-08"},"_buckets":{"deposit":"6807df73-a61d-4aac-82e2-b713383c63c3"},"_deposit":{"id":"231641","pid":{"type":"depid","value":"231641","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"固有表現アノテーションにおける画面操作記録を用いた不良回答検出","author_link":["625678","625679","625680","625677"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"固有表現アノテーションにおける画面操作記録を用いた不良回答検出"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"機械学習・大規模言語モデル","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-01-08","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"奈良先端科学技術大学院大学"},{"subitem_text_value":"奈良先端科学技術大学院大学"},{"subitem_text_value":"奈良先端科学技術大学院大学"},{"subitem_text_value":"奈良先端科学技術大学院大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/231641/files/IPSJ-HCI24206040.pdf","label":"IPSJ-HCI24206040.pdf"},"date":[{"dateType":"Available","dateValue":"2026-01-08"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-HCI24206040.pdf","filesize":[{"value":"3.1 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":"33"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"cd555cc7-5000-4aff-b0e4-46af79fcc643","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"福光, 嘉伸"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"松田, 裕貴"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"諏訪, 博彦"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"安本, 慶一"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA1221543X","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8760","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"アノテーション作業をクラウドソーシングで行うことにより，低コストで機械学習のための学習データを収集できる．しかし，得られるデータの品質に大きなばらつきがあり，対価として報酬を付与すると可能な限り速く回答を行おうとする行動によって不良回答が発生する問題がある．そこで，本研究ではアノテーションタスクを対象として不良回答をリアルタイムで検出することを目的とし，作業中の画面操作から得られるカーソル移動量や操作時間などの特徴量を用いた検出手法を提案する．本稿では，適切回答・不良回答の分類を行い，精度を評価するとともに分類において重要な特徴量について分析を行う．機械学習モデルによる分類では，0.738 の Accuracy が得られ，ラベル付与数と，ラベル付与毎の平均カーソル移動量・クリック回数が，分類において重要であることが分かった．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告ヒューマンコンピュータインタラクション（HCI）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-01-08","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"40","bibliographicVolumeNumber":"2024-HCI-206"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T10:40:52.354949+00:00","created":"2025-01-19T01:32:03.874926+00:00","links":{},"id":231641}