{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229215","sets":["1164:6757:11095:11361"]},"path":["11361"],"owner":"44499","recid":"229215","title":["位相幾何学に基づくIsomapのパラメーター決定法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-11-09"},"_buckets":{"deposit":"aa890670-06b4-4079-8d5f-7b6f862df2bf"},"_deposit":{"id":"229215","pid":{"type":"depid","value":"229215","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"位相幾何学に基づくIsomapのパラメーター決定法","author_link":["615999","616002","616001","616000"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"位相幾何学に基づくIsomapのパラメーター決定法"},{"subitem_title":"Parameter determination method for Isomap based on topological geometry","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2023-11-09","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"島根大学大学院自然科学研究科"},{"subitem_text_value":"島根大学大学院自然科学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Natural Science and Technology,Shimane University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Natural Science and Technology,Shimane 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/229215/files/IPSJ-DCC23035048.pdf","label":"IPSJ-DCC23035048.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DCC23035048.pdf","filesize":[{"value":"2.1 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"50"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"44aafa22-e106-4f04-9cef-8053eb53fc83","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 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":"須山, 未侑羅"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"坂野, 鋭"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Suyama, Miura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hitoshi, Sakano","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12628338","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":"2188-8868","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本研究では，高次元データを人間が理解可能な 2，3  次元に圧縮するための非線形次元圧縮法，Isomap の近傍パラメータの決定方法を提案する．画像などの高次元データは人間にとって知覚が難しく，線形変換では十分な分析が難しいため，非線形次元圧縮が用いられることが多い．しかし，これらの方法には任意性のあるパラメータが存在し，その決定が問題となる．そこで，位相的データ解析の一環として発展してきたパーシステントホモロジー技術を活用し，高次元空間の分布形状を数値的に捉え，次元圧縮のパラメータ決定のヒントを提供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":"In this study, we propose a method to determine the neighborhood parameters of Isomap, a nonlinear dimensionality reduction technique, to compress high-dimensional data into 2 or 3 dimensions that humans can understand. High-dimensional data, such as images, are challenging for humans to perceive, and linear transformations often fall short in providing adequate analysis. As a result, nonlinear dimensionality reduction methods are frequently used. However, these methods come with arbitrary parameters, making their determination a challenge. To address this, we leverage persistent homology technology, which has evolved as part of topological data analysis. This technology numerically captures the distribution shape in high-dimensional spaces and offers insights into parameter determination for dimensionality reduction.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告デジタルコンテンツクリエーション（DCC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2023-11-09","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"48","bibliographicVolumeNumber":"2023-DCC-35"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":229215,"updated":"2025-01-19T11:35:55.875894+00:00","links":{},"created":"2025-01-19T01:28:20.060328+00:00"}