{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00159457","sets":["1164:4179:8454:8706"]},"path":["8706"],"owner":"11","recid":"159457","title":["様々な分野における対訳コーパスを用いた構文解析器の自己学習効果の検証"],"pubdate":{"attribute_name":"公開日","attribute_value":"2016-05-09"},"_buckets":{"deposit":"375412d0-8d11-457d-91c3-5cbb5ec1c348"},"_deposit":{"id":"159457","pid":{"type":"depid","value":"159457","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"様々な分野における対訳コーパスを用いた構文解析器の自己学習効果の検証","author_link":["307180","307181","307183","307182","307179"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"様々な分野における対訳コーパスを用いた構文解析器の自己学習効果の検証"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"自然言語処理","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2016-05-09","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情報科学研究科"},{"subitem_text_value":"奈良先端科学技術大学院大学情報科学研究科"},{"subitem_text_value":"奈良先端科学技術大学院大学情報科学研究科"},{"subitem_text_value":"奈良先端科学技術大学院大学情報科学研究科"},{"subitem_text_value":"奈良先端科学技術大学院大学情報科学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Information Science, Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science, Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science, Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science, Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science, 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/159457/files/IPSJ-NL16226008.pdf","label":"IPSJ-NL16226008.pdf"},"date":[{"dateType":"Available","dateValue":"2018-05-09"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-NL16226008.pdf","filesize":[{"value":"376.8 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":"f76d61a8-0ea0-4b33-be15-d01199409dc2","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2016 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"森下, 睦"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小田, 悠介"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Graham, Neubig"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"吉野, 幸一郎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中村, 哲"}],"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":"本稿では，対訳コーパス，統語ベース翻訳器，機械翻訳の自動評価尺度を用いて，自己学習データを選択した上で構文解析器の自己学習を行う手法を，様々な分野を対象に適用しその効果を検証する．本手法では構文木データを新たに人手で作成する必要が無く，対訳コーパスのみを用いて構文解析器を向上させられる利点がある．実験の結果，11 種類中 4 種類のドメインにおいて，本手法がベースラインと比較して構文解析精度を有意に向上させることが分かった．また，提案手法による性能向上が最も期待できるドメインの特徴について調査した．なお，本実験で作成したモデルは今後公開する予定である．","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":"2016-05-09","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"8","bibliographicVolumeNumber":"2016-NL-226"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":159457,"updated":"2025-01-20T12:41:23.242328+00:00","links":{},"created":"2025-01-19T00:32:29.429314+00:00"}