{"id":211712,"created":"2025-01-19T01:12:51.094593+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00211712","sets":["1164:5352:10544:10612"]},"path":["10612"],"owner":"44499","recid":"211712","title":["情報幾何を用いた時系列データの布置"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-06-21"},"_buckets":{"deposit":"7d0811e7-3ec1-46aa-8cb9-980473655010"},"_deposit":{"id":"211712","pid":{"type":"depid","value":"211712","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"情報幾何を用いた時系列データの布置","author_link":["538318","538315","538320","538319","538316","538317"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"情報幾何を用いた時系列データの布置"},{"subitem_title":"Constellation of time dependent data using information geometry","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"学習理論","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2021-06-21","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"早稲田大学先進理工学研究科"},{"subitem_text_value":" 株式会社リクルート"},{"subitem_text_value":"早稲田大学先進理工学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Faculty of Science and Engineering, Waseda University","subitem_text_language":"en"},{"subitem_text_value":"Recruit Co., Ltd.","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Science and Engineering, Waseda 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/211712/files/IPSJ-BIO21066009.pdf","label":"IPSJ-BIO21066009.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-BIO21066009.pdf","filesize":[{"value":"3.9 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"41"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"8ea62f47-0b2f-4de3-8541-ff53d1cf4b3b","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":"杉浦, 太樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"布施, 拓馬"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"村田, 昇"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Taiki, Sugiura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takuma, Fuse","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Noboru, Murata","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12055912","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":"2188-8590","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"大量かつ高次元のデータからの知見獲得や，データの構造理解を行うにあたって布置は重要な技術である． 本稿では複数時刻に渡って観測されている時系列データに注目した布置手法の提案を行う．布置手法として特によく用いられている SNE を時系列データに対して各時刻に適用すると，結果は時系列構造の変化を適切に表現できない． 本稿では時系列データの布置を，モデル多様体上の確率分布の平滑化として問題を定式化することで，時系列構造の変化を表現した布置ができることを示す．また既存の布置手法では表現できていない時系列の変化に伴うデータの追加と消失についても提案を行う．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Constellation is an essential technique for gaining knowledge from large amounts of high-dimensional data and understanding data structure. In this paper, we propose a constellation method focusing on time-series data observed over multiple periods. If we apply SNE, which is one of the commonly used methods, to the time series data each time, the result cannot correctly represent the change of the time series structure. In this paper, we formulate the problem as a smoothing of probability distributions on a model manifold and show that it can represent changes in time series data structure. We also propose a method to represent the addition and loss of data due to the time series change, which existing methods cannot represent.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告バイオ情報学（BIO）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-06-21","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"9","bibliographicVolumeNumber":"2021-BIO-66"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T17:42:29.580970+00:00","links":{}}