{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00214093","sets":["1164:4179:10535:10759"]},"path":["10759"],"owner":"44499","recid":"214093","title":["マルチラベル分類における共起情報を用いたラベル平滑化手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-11-24"},"_buckets":{"deposit":"c11cf414-ab09-4b6d-9a94-485517ccd121"},"_deposit":{"id":"214093","pid":{"type":"depid","value":"214093","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"マルチラベル分類における共起情報を用いたラベル平滑化手法","author_link":["548616","548620","548618","548619","548622","548621","548617","548623"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"マルチラベル分類における共起情報を用いたラベル平滑化手法"},{"subitem_title":"Label smoothing with co-occurrence information for multi-label classification","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"データ拡張・ラベリング","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2021-11-24","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"日本放送協会放送技術研究所"},{"subitem_text_value":"日本放送協会放送技術研究所／東京工業大学情報理工学院"},{"subitem_text_value":"日本放送協会放送技術研究所"},{"subitem_text_value":"日本放送協会放送技術研究所"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Science and Technology Research Laboratories, NHK","subitem_text_language":"en"},{"subitem_text_value":"Science and Technology Research Laboratories, NHK / School of Computing, Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Science and Technology Research Laboratories, NHK","subitem_text_language":"en"},{"subitem_text_value":"Science and Technology Research Laboratories, NHK","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/214093/files/IPSJ-NL21251030.pdf","label":"IPSJ-NL21251030.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-NL21251030.pdf","filesize":[{"value":"1.5 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"23"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"e105e262-22b6-42ff-b147-f6aee1deae54","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 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":"安田, 有希"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"石渡, 大智"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"宮﨑, 太郎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"後藤, 淳"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yuki, Yasuda","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Taichi, Ishiwatari","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Taro, Miyazaki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Jun, Goto","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_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":"マルチラベル分類のなかでも，ラベルの出現頻度が不均衡な分布であるデータセットを用いた学習は重要な課題の一つである．そのような不均衡データセットを用いた学習では，低頻度ラベルに対応する入力サンプルが少ないことから，モデルの低頻度ラベルに対する精度が低下してしまう．そこで，本研究では各ラベルの共起 情報をラベル平滑化手法に取り込み，低頻度ラベルであっても関連した入力サンプルで学習を可能とする手法を提 案する．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Imbalanced learning is one of the big issues in multi-label classification task. Training models using such imbalanced distribution of labels can cause overfitting to low-frequency labels because of lack of samples related to such labels. To tackle this issue, we propose a novel method for creating a soft target that represents the strength of label relationships, which is inspired by widely-used approaches, considering label co-occurrences and label smoothing. The result of the experiment shows that proposed method outperforms each baseline method, especially in terms of low-frequency labels.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告自然言語処理（NL）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-11-24","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"30","bibliographicVolumeNumber":"2021-NL-251"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":214093,"updated":"2025-01-19T16:54:17.867639+00:00","links":{},"created":"2025-01-19T01:14:55.661681+00:00"}