{"created":"2025-01-19T01:17:04.330610+00:00","updated":"2025-01-19T15:50:21.141505+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00216464","sets":["1164:4402:10858:10859"]},"path":["10859"],"owner":"44499","recid":"216464","title":["Automatic Short Answer Grading with Rubric-based Semantic Embedding Optimization"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-02-14"},"_buckets":{"deposit":"367870f9-0a9b-49a8-bea3-f88d30ad7cc1"},"_deposit":{"id":"216464","pid":{"type":"depid","value":"216464","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Automatic Short Answer Grading with Rubric-based Semantic Embedding Optimization","author_link":["558867","558871","558870","558868","558866","558869"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Automatic Short Answer Grading with Rubric-based Semantic Embedding Optimization"},{"subitem_title":"Automatic Short Answer Grading with Rubric-based Semantic Embedding Optimization","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2022-02-14","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Kyushu Universtiy"},{"subitem_text_value":"The National Center for University Entrance Examinations"},{"subitem_text_value":"Kyushu Universtiy"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Kyushu Universtiy","subitem_text_language":"en"},{"subitem_text_value":"The National Center for University Entrance Examinations","subitem_text_language":"en"},{"subitem_text_value":"Kyushu Universtiy","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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/216464/files/IPSJ-ICS22205011.pdf","label":"IPSJ-ICS22205011.pdf"},"date":[{"dateType":"Available","dateValue":"2024-02-14"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ICS22205011.pdf","filesize":[{"value":"2.1 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":"25"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"ea37ebe3-8601-450d-8cc2-5e972eda7a01","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Bo, Wang"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tsunenori, Ishioka"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tsunenori, Mine"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Bo, Wang","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tsunenori, Ishioka","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tsunenori, Mine","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11135936","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":"2188-885X","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Large-scaled encoders such as BERT have been actively used for sentence embedding in automatic scoring. However, the embedding may not be optimal due to non-uniform vector distribution. By conducting fast contrastive learning, methods like SBERT got better semantic embeddings and were actively used in textual similarity datasets. However, the cost to obtain the similarities limits its application to automatic grading. In this paper, we propose a method of calculating similarity from the rubric to perform contrastive learning for a better semantic embedding. We conducted extensive experiments on 60,000 answer/question data for three independent questions. The experimental results show that the proposed method outperforms all baselines in terms of accuracy and computation time.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Large-scaled encoders such as BERT have been actively used for sentence embedding in automatic scoring. However, the embedding may not be optimal due to non-uniform vector distribution. By conducting fast contrastive learning, methods like SBERT got better semantic embeddings and were actively used in textual similarity datasets. However, the cost to obtain the similarities limits its application to automatic grading. In this paper, we propose a method of calculating similarity from the rubric to perform contrastive learning for a better semantic embedding. We conducted extensive experiments on 60,000 answer/question data for three independent questions. The experimental results show that the proposed method outperforms all baselines in terms of accuracy and computation time.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告知能システム（ICS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-02-14","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"11","bibliographicVolumeNumber":"2022-ICS-205"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":216464,"links":{}}