{"created":"2024-12-12T10:04:08.279250+00:00","id":2011248,"links":{},"metadata":{"_buckets":{"deposit":"6b4b0187-0477-491c-b391-c8cd43d89aa2"},"_deposit":{"created_by":7,"id":"2011248","owners":[7],"pid":{"revision_id":0,"type":"depid","value":"2011248"},"status":"published"},"_oai":{"id":"oai:tokushima-u.repo.nii.ac.jp:02011248","sets":["1713853213384:1713853295607"]},"author_link":["401","769"],"item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2023-05-23","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicPageEnd":"507","bibliographicPageStart":"493","bibliographicVolumeNumber":"15","bibliographic_titles":[{"bibliographic_title":"IEEE Transactions on Affective Computing","bibliographic_titleLang":"en"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"For text sentiment analysis, state-of-the-art neural language models have demonstrated promising performance. However, they lack interpretability, require vast volumes of annotated data, and are typically specialized for tasks. In this paper, we explore a connection between fine-tuned Transformer models and unsupervised LDA approach to cope with text sentiment analysis tasks, inspired by the concept of Neuro-symbolic AI. The Transformer and LDA models are combined as a feature extractor to extract the hidden representations of the input text sequences. Subsequently, we employ a feedforward network to forecast various sentiment analysis tasks, such as multi-label emotion prediction, dialogue quality prediction, and nugget detection. Our proposed method obtains the best results in the NTCIR-16 dialogue evaluation (DialEval-2) task, as well as cutting-edge results in emotional intensity prediction using the Ren_CECps corpus. Extensive experiments show that our proposed method is highly explainable, cost-effective in training, and superior in terms of accuracy and robustness.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"IEEE","subitem_publisher_language":"en"}]},"item_10001_rights_15":{"attribute_name":"権利情報","attribute_value_mlt":[{"subitem_rights":"© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.","subitem_rights_language":"en"}]},"item_10001_source_id_9":{"attribute_name":"収録物ID","attribute_value_mlt":[{"subitem_source_identifier":"19493045","subitem_source_identifier_type":"ISSN"}]},"item_10001_version_type_20":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_be7fb7dd8ff6fe43","subitem_version_type":"NA"}]},"item_1715043197608":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"embargoed access"}]},"item_1722929371688":{"attribute_name":"出版社版DOI","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_language":"ja","subitem_relation_name_text":"10.1109/TAFFC.2023.3279318"}],"subitem_relation_type_id":{"subitem_relation_type_id_text":"https://doi.org/10.1109/TAFFC.2023.3279318","subitem_relation_type_select":"DOI"}}]},"item_1723180141928":{"attribute_name":"EID","attribute_value_mlt":[{"subitem_identifier_type":"URI","subitem_identifier_uri":"396930"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Ding, Fei","creatorNameLang":"en"}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"","affiliationNameIdentifierScheme":"ISNI","affiliationNameIdentifierURI":"http://www.isni.org/isni/"}],"affiliationNames":[{"affiliationName":"","affiliationNameLang":"ja"}]}],"creatorNames":[{"creatorName":"康, 鑫","creatorNameLang":"ja"},{"creatorName":"コウ, シン","creatorNameLang":"ja-Kana"},{"creatorName":"Kang, Xin","creatorNameLang":"en"}],"familyNames":[{"familyName":"康","familyNameLang":"ja"},{"familyName":"コウ","familyNameLang":"ja-Kana"},{"familyName":"Kang","familyNameLang":"en"}],"givenNames":[{"givenName":"鑫","givenNameLang":"ja"},{"givenName":"シン","givenNameLang":"ja-Kana"},{"givenName":"Xin","givenNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"769","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"292960/profile-ja.html","nameIdentifierScheme":"徳島大学 教育研究者総覧","nameIdentifierURI":"http://pub2.db.tokushima-u.ac.jp/ERD/person/292960/profile-ja.html"}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"","affiliationNameIdentifierScheme":"ISNI","affiliationNameIdentifierURI":"http://www.isni.org/isni/"}],"affiliationNames":[{"affiliationName":"","affiliationNameLang":"ja"}]}],"creatorNames":[{"creatorName":"任, 福継","creatorNameLang":"ja"},{"creatorName":"ニン, フジ","creatorNameLang":"ja-Kana"},{"creatorName":"Ren, Fuji","creatorNameLang":"en"}],"familyNames":[{"familyName":"任","familyNameLang":"ja"},{"familyName":"ニン","familyNameLang":"ja-Kana"},{"familyName":"Ren","familyNameLang":"en"}],"givenNames":[{"givenName":"福継","givenNameLang":"ja"},{"givenName":"フジ","givenNameLang":"ja-Kana"},{"givenName":"Fuji","givenNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"401","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"19966/profile-ja.html","nameIdentifierScheme":"徳島大学 教育研究者総覧","nameIdentifierURI":"http://pub2.db.tokushima-u.ac.jp/ERD/person/19966/profile-ja.html"},{"nameIdentifier":"20264947","nameIdentifierScheme":"e-Rad","nameIdentifierURI":"https://nrid.nii.ac.jp/ja/search/?qm=20264947"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2025-05-23"}],"displaytype":"detail","filename":"taffc_15_2_493.pdf","filesize":[{"value":"2.07 MB"}],"format":"application/pdf","mimetype":"application/pdf","url":{"objectType":"fulltext","url":"https://tokushima-u.repo.nii.ac.jp/record/2011248/files/taffc_15_2_493.pdf"},"version_id":"57e3a19c-78ba-4913-bed5-e41828dce340"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Neuro-symbolic AI","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Sentiment Analysis","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Fine-tuned Transformer","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Latent Dirichlet Allocation","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Neuro or Symbolic? Fine-tuned Transformer with Unsupervised LDA Topic Clustering for Text Sentiment Analysis","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Neuro or Symbolic? Fine-tuned Transformer with Unsupervised LDA Topic Clustering for Text Sentiment Analysis","subitem_title_language":"en"}]},"item_type_id":"40001","owner":"7","path":["1713853295607"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2023-10-11"},"publish_date":"2023-10-11","publish_status":"0","recid":"2011248","relation_version_is_last":true,"title":["Neuro or Symbolic? Fine-tuned Transformer with Unsupervised LDA Topic Clustering for Text Sentiment Analysis"],"weko_creator_id":"7","weko_shared_id":-1},"updated":"2025-02-13T05:58:25.111138+00:00"}