{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00235665","sets":["6504:11678:11697"]},"path":["11697"],"owner":"44499","recid":"235665","title":["位相的データ解析に基づく言語モデルが生成する埋め込みベクトルの特徴抽出"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-03-01"},"_buckets":{"deposit":"117ef471-3481-497c-88e4-65ea37ec20a3"},"_deposit":{"id":"235665","pid":{"type":"depid","value":"235665","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"位相的データ解析に基づく言語モデルが生成する埋め込みベクトルの特徴抽出","author_link":["644015"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"位相的データ解析に基づく言語モデルが生成する埋め込みベクトルの特徴抽出"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ソフトウェア科学・工学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2024-03-01","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"パーソルキャリア"}]},"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/235665/files/IPSJ-Z86-2A-03.pdf","label":"IPSJ-Z86-2A-03.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-03"}],"format":"application/pdf","filename":"IPSJ-Z86-2A-03.pdf","filesize":[{"value":"212.3 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"b60597f6-6c47-46f1-9b49-07092f2a274c","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"佐藤, 哲"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"自然言語処理では、単語や文章を数値のベクトルで表現する手法が一般的である.しかし,言語モデルの大規模化と自然言語を表すベクトルの高次元化により,出力されたベクトルの意味を理解することが難しくなっている.そこで本研究では,高次元ベクトルを多数の低次元ベクトルの集合で表す手法を導入し,低次元ベクトル集合の幾何的な特徴を抽出することで,効果的に元の高次元ベクトルの特徴量を抽出する手法を提案する.","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"110","bibliographic_titles":[{"bibliographic_title":"第86回全国大会講演論文集"}],"bibliographicPageStart":"109","bibliographicIssueDates":{"bibliographicIssueDate":"2024-03-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":235665,"updated":"2025-01-19T09:34:08.667032+00:00","links":{},"created":"2025-01-19T01:37:16.182336+00:00"}