{"links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00230143","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"230143","title":["半教師あり学習を用いた記述式問題の自動採点における根拠箇所提示"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"ce7e004a-0a70-414c-9bc6-f7b14545823d"},"_deposit":{"id":"230143","pid":{"type":"depid","value":"230143","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"半教師あり学習を用いた記述式問題の自動採点における根拠箇所提示","author_link":["619174","619173"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"半教師あり学習を用いた記述式問題の自動採点における根拠箇所提示"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人工知能と認知科学","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":"横浜国大"},{"subitem_text_value":"横浜国大"}]},"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/230143/files/IPSJ-Z85-2V-09.pdf","label":"IPSJ-Z85-2V-09.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-2V-09.pdf","filesize":[{"value":"634.7 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"d575a5c2-58f4-4dd0-b108-9d7b0ac9b56d","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":"須田, 匠"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"濱上, 知樹"}],"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，各種試験への記述式問題の導入が進んでいる。これに伴い，オンライン上で記述式問題の答案を自動的に採点・フィードバックする学習システムへの需要が高まっている。従来の自動採点システムには，機械学習を用いてサンプル答案と採点結果を分析し，人力での採点を模倣するものがある。しかし，事前の学習に十分な数の答案や採点結果を収集することは必ずしも可能ではない。本研究では，少数の答案を教師データとして用いるフィードバック可能な自動採点機構として，半教師あり機械学習により採点の根拠となる答案文中のフレーズを推定する手法を提案する。また，多数の答案を教師データとして用いる手法と比較し，本手法の有効性を示した。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"712","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"711","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:29:43.675492+00:00","updated":"2025-01-19T11:16:22.896265+00:00","id":230143}