{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00218751","sets":["1164:4402:10858:10955"]},"path":["10955"],"owner":"44499","recid":"218751","title":["機械学習モデルを使用したKyutechコーパスのトピック分類"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-07-01"},"_buckets":{"deposit":"7fa044e4-11d9-4aef-8a78-8ac9f810ceb8"},"_deposit":{"id":"218751","pid":{"type":"depid","value":"218751","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"機械学習モデルを使用したKyutechコーパスのトピック分類","author_link":["569561","569560","569562","569563"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"機械学習モデルを使用したKyutechコーパスのトピック分類"},{"subitem_title":"Topic Classification of Kyutech Corpus by Machine Learning","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"分析","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-07-01","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"九州工業大学大学院情報工学府情報創成工学専攻"},{"subitem_text_value":"九州工業大学大学院情報工学研究院知能情報工学研究系 "}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Creative Informatics, Kyushu Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Department of Artificial Intelligence, Kyushu Institute of 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/218751/files/IPSJ-ICS22207006.pdf","label":"IPSJ-ICS22207006.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ICS22207006.pdf","filesize":[{"value":"976.2 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"25"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"4bf6b57e-18e8-40dc-9622-f6f8803bf387","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"川嵜, 慎乃介"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"嶋田, 和孝"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shinnosuke, Kawasaki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kazutaka, Shimada","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11135936","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":"2188-885X","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"複数人議論を行う際，議事録は決定事項の記録や非参加者への情報共有のために必要不可欠である．議論の自動議事録生成のためには，議論の文脈に沿った話題（トピック）を捉えることが第一に必要である．そこで，本研究では発話単位のトピック分類に取り組む．データセットには複数人議論コーパスである Kyutech コーパスを使用する．Kyutech コーパスでは 1 発話に複数のトピックタグが付与されている場合がある．したがって，トピック分類では，そのうち一つを正しく推定する多値分類と全てのタグを正しく推定するマルチラベル分類の 2 種類の問題を取り扱う．複数の機械学習技術を適用し，その有効性を比較，検証する．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Discussion summarization is one of the most important tasks for discussion analysis. Utterances in a discussion contains several topics, and the topics have an important role for the summarization. In this paper, we report a topic classification task of utterances in a multi-party discussion corpus: Kyutech corpus. In the corpus, each utterance contains one to three topic tags. We compare several machine learning methods for the topic tag classification task.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告知能システム（ICS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-07-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"6","bibliographicVolumeNumber":"2022-ICS-207"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":218751,"updated":"2025-01-19T15:02:54.510851+00:00","links":{},"created":"2025-01-19T01:19:05.955574+00:00"}