{"created":"2022-02-02T02:11:08.059497+00:00","id":2012487,"links":{},"metadata":{"_buckets":{"deposit":"e1375d65-1d03-4caa-bc4f-1e6a6601d71b"},"_deposit":{"id":"2012487","owners":[1],"pid":{"revision_id":0,"type":"depid","value":"2012487"},"status":"published"},"_oai":{"id":"oai:u-ryukyu.repo.nii.ac.jp:02012487","sets":["1642838163960:1642838338003","1642838403551:1642838406845"]},"author_link":[],"item_1617186331708":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Graph Convolutionにより構文構造を加味したGANによる文章生成手法の提案","subitem_1551255648112":"ja"}]},"item_1617186419668":{"attribute_name":"Creator","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"澤崎, 夏希","creatorNameLang":"ja"}]},{"creatorNames":[{"creatorName":"遠藤, 聡志","creatorNameLang":"ja"}]},{"creatorNames":[{"creatorName":"當間, 愛晃","creatorNameLang":"ja"}]},{"creatorNames":[{"creatorName":"山田, 孝治","creatorNameLang":"ja"}]},{"creatorNames":[{"creatorName":"赤嶺, 有平","creatorNameLang":"ja"}]}]},"item_1617186476635":{"attribute_name":"Access Rights","attribute_value_mlt":[{"subitem_1522299639480":"open access","subitem_1600958577026":"http://purl.org/coar/access_right/c_abf2"}]},"item_1617186609386":{"attribute_name":"Subject","attribute_value_mlt":[{"subitem_1522299896455":"ja","subitem_1522300014469":"Other","subitem_1523261968819":"かさ増し"},{"subitem_1522299896455":"ja","subitem_1522300014469":"Other","subitem_1523261968819":"自然言語"},{"subitem_1522299896455":"ja","subitem_1522300014469":"Other","subitem_1523261968819":"不均衡データ"},{"subitem_1522299896455":"en","subitem_1522300014469":"Other","subitem_1523261968819":"GAN"},{"subitem_1522299896455":"en","subitem_1522300014469":"Other","subitem_1523261968819":"GCN"}]},"item_1617186626617":{"attribute_name":"Description","attribute_value_mlt":[{"subitem_description":"現在ディープラーニングの発展により様々な問題が解決されているが，その問題の多くは十分なデータ 量が確保されており，少量学習データでの問題解決は依然として課題となっている．データ量が少ない場合の対 策として，データを増加させるかさ増し手法が用いられる．特に画像分野においては Generative Adversarial Network:GAN を用いた高精度な画像生成手法が注目されている．自然言語の分野においても，GAN を応用し文 章を生成する試みが広く行われているが，十分な精度の文章生成を行うのは難しい．原因の一つとして，自然言語 生成に用いられる GAN では，多くの場合構文構造は加味されていないことがあげられる．そこで，本論文では グラフ構造を畳み込む Graph Convolution を用いて，構文構造を加味した上で文章生成を行う手法を提案する．","subitem_description_type":"Other"},{"subitem_description":"論文","subitem_description_type":"Other"}]},"item_1617186643794":{"attribute_name":"Publisher","attribute_value_mlt":[{"subitem_1522300295150":"ja","subitem_1522300316516":"Webインテリジェンスとインタラクション研究会"}]},"item_1617186702042":{"attribute_name":"Language","attribute_value_mlt":[{"subitem_1551255818386":"jpn"}]},"item_1617186783814":{"attribute_name":"Identifier","attribute_value_mlt":[{"subitem_identifier_type":"HDL","subitem_identifier_uri":"http://hdl.handle.net/20.500.12000/46168"}]},"item_1617186941041":{"attribute_name":"Source Title","attribute_value_mlt":[{"subitem_1522650068558":"ja","subitem_1522650091861":"第13回研究会オンライン・プロシーディングス"}]},"item_1617187056579":{"attribute_name":"Bibliographic Information","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2018-12-03","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"44","bibliographicPageStart":"39"}]},"item_1617258105262":{"attribute_name":"Resource Type","attribute_value_mlt":[{"resourcetype":"conference paper","resourceuri":"http://purl.org/coar/resource_type/c_5794"}]},"item_1617265215918":{"attribute_name":"Version Type","attribute_value_mlt":[{"subitem_1522305645492":"VoR","subitem_1600292170262":"http://purl.org/coar/version/c_970fb48d4fbd8a85"}]},"item_1617605131499":{"attribute_name":"File","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","filename":"WI2-2018-18.pdf","mimetype":"application/pdf","url":{"objectType":"fulltext","url":"https://u-ryukyu.repo.nii.ac.jp/record/2012487/files/WI2-2018-18.pdf"},"version_id":"b211eff3-12fb-4817-938c-fd371b542422"}]},"item_title":"Graph Convolutionにより構文構造を加味したGANによる文章生成手法の提案","item_type_id":"15","owner":"1","path":["1642838338003","1642838406845"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2020-06-17"},"publish_date":"2020-06-17","publish_status":"0","recid":"2012487","relation_version_is_last":true,"title":["Graph Convolutionにより構文構造を加味したGANによる文章生成手法の提案"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-08-03T05:27:06.248467+00:00"}