{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00212207","sets":["1164:4179:10535:10649"]},"path":["10649"],"owner":"44499","recid":"212207","title":["日本語SentenceBERTの構築とその評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-07-20"},"_buckets":{"deposit":"cd97d0b9-fd30-42d4-b465-fa0c63b7be0b"},"_deposit":{"id":"212207","pid":{"type":"depid","value":"212207","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"日本語SentenceBERTの構築とその評価","author_link":["540898","540901","540899","540900"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"日本語SentenceBERTの構築とその評価"},{"subitem_title":"Construction and Evaluation of Japanese Sentence-BERT Models","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2021-07-20","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"茨城大学大学院理工学研究科情報工学専攻"},{"subitem_text_value":"茨城大学大学院理工学研究科情報科学領域"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Major in Computer and Information Sciences, Graduate School of Science and Engineering, Ibaraki University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Science and Engineering, Department of Computer and Information Sciences, Ibaraki University","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/212207/files/IPSJ-NL21249007.pdf","label":"IPSJ-NL21249007.pdf"},"date":[{"dateType":"Available","dateValue":"2023-07-20"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-NL21249007.pdf","filesize":[{"value":"434.8 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"23"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"8212f3f4-c5aa-4ee5-8bb8-f54e7f6ea599","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"芝山, 直希"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"新納, 浩幸"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Naoki, Shibayama","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hiroyuki, Shinnou","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10115061","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":"2188-8779","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"SentenceBERT は文の埋め込み表現の構築に特化した BERT である．BERT のように意味の解析能力を有している一方，BERT とは異なりオンラインで実行する必要がないため，類似文検索などでの有用性が高い．しかし，現在，適切な形で公開されてる日本語 SentenceBERT モデルは存在しない．そこでここでは京都大学で公開されている日本語版 SNLI（JSNLI）と公開されている日本語 BERT モデル 6 つを用いて 6 つの日本語 SentenceBERT を構築した．また SentenceBERT モデルの評価方法として，クラス内分散とクラス間分散の比を測る方法，及び k-NN 法による単純な分類器での文の分類問題に対する精度を用いる方法を提案し，作成した 6 つの日本語 SentenceBERT を評価した．結果，東北大版 BERT と NICT 版 BERT から構築した SentenceBERT が同程度の高い性能を示した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告自然言語処理（NL）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-07-20","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"7","bibliographicVolumeNumber":"2021-NL-249"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":212207,"updated":"2025-01-19T17:34:31.338642+00:00","links":{},"created":"2025-01-19T01:13:12.108876+00:00"}