{"id":48696,"updated":"2025-01-22T08:23:27.891474+00:00","links":{},"created":"2025-01-18T23:13:52.909524+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00048696","sets":["1164:4179:4236:4242"]},"path":["4242"],"owner":"1","recid":"48696","title":["学習型機械翻訳手法GA - ILMTにおける状態遷移の導入について"],"pubdate":{"attribute_name":"公開日","attribute_value":"2000-01-27"},"_buckets":{"deposit":"eaff9eea-2db9-44c6-a8b8-2ab2806053c5"},"_deposit":{"id":"48696","pid":{"type":"depid","value":"48696","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"学習型機械翻訳手法GA - ILMTにおける状態遷移の導入について","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"学習型機械翻訳手法GA - ILMTにおける状態遷移の導入について"},{"subitem_title":"Using State Transition on GA - ILMT based Learning Capability","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2000-01-27","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"北海学園大学工学部電子情報工学科"},{"subitem_text_value":"北海道大学大学院工学研究科電子情報工学専攻"},{"subitem_text_value":"北海学園大学工学部電子情報工学科"},{"subitem_text_value":"北海道大学大学院工学研究科電子情報工学専攻"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Dept. of Electronics and Information, Hokkai - Gakuen University","subitem_text_language":"en"},{"subitem_text_value":"Division of Electronics and Information, Hokkaido University","subitem_text_language":"en"},{"subitem_text_value":"Dept. of Electronics and Information, Hokkai - Gakuen University","subitem_text_language":"en"},{"subitem_text_value":"Division of Electronics and Information, Hokkaido 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/48696/files/IPSJ-NL99135023.pdf"},"date":[{"dateType":"Available","dateValue":"2002-01-27"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-NL99135023.pdf","filesize":[{"value":"683.8 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":"ba9a4a95-64d7-426c-af2d-d7bb778fdec2","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2000 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"越前谷, 博"},{"creatorName":"荒木, 健治"},{"creatorName":"桃内, 佳雄"},{"creatorName":"栃内, 香次"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hiroshi, Echizen-Ya","creatorNameLang":"en"},{"creatorName":"Kenji, Araki","creatorNameLang":"en"},{"creatorName":"Yoshio, Momouchi","creatorNameLang":"en"},{"creatorName":"Koji, Tochinai","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_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"我々は，これまでに与えられた翻訳例のみから翻訳ルールを自動的に獲得することにより翻訳を行う学習型機械翻訳手法として，遺伝的アルゴリズムを適用した帰納的学習による機械翻訳手法(GA-ILMT)を提案している．しかし，学習という観点から本手法は十分な能力を備えるまでには至っておらず，その結果として，翻訳精度もまた不十分であった．そこで，我々は，このGA-ILMTにおいて，解析的な知識を明示的に与えることなく，学習能力の向上という観点からの改良を試みた．即ち，システム自身が獲得した翻訳ルールを階層的に処理することにより翻訳を行う能力の実現である．そのために，我々は状態遷移を導入した．状態遷移を導入することにより，システム自身が翻訳結果の生成過程に着目した翻訳を行う．本稿では，GA-ILMTにおける状態遷移の導入とその有効性について述べる．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"We previously proposed a method of machine translation using inductive learning with genetic algorithms (GA-ILMT) based on learning capability. However, its learning capability is not enough. As the result, its translation qulaity is still low. We used a state transition to improve the learning capability of GA-ILMT. GA-ILMT using the state transition can perform translation based on the process of a translation without using any analyitical knowledge. In this paper, we will describe the use of state transition on GA-ILMT and describe an effectiveness of the state transition.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"180","bibliographic_titles":[{"bibliographic_title":"情報処理学会研究報告自然言語処理（NL）"}],"bibliographicPageStart":"173","bibliographicIssueDates":{"bibliographicIssueDate":"2000-01-27","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"11(1999-NL-135)","bibliographicVolumeNumber":"2000"}]},"relation_version_is_last":true,"weko_creator_id":"1"}}