{"created":"2025-01-19T01:42:19.707913+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00238959","sets":["1164:1165:11462:11709"]},"path":["11709"],"owner":"44499","recid":"238959","title":["自動ファクトチェックのためのLLMを用いた検証可能クレーム判定手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-09-04"},"_buckets":{"deposit":"d102151f-cc48-4824-8b26-2610caa4e16b"},"_deposit":{"id":"238959","pid":{"type":"depid","value":"238959","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"自動ファクトチェックのためのLLMを用いた検証可能クレーム判定手法","author_link":["654532","654533","654531","654534"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"自動ファクトチェックのためのLLMを用いた検証可能クレーム判定手法"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"2B オーガナイズドセッション 偽情報対策技術","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-09-04","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"富士通株式会社データ＆セキュリティ研究所"},{"subitem_text_value":"富士通株式会社データ＆セキュリティ研究所"},{"subitem_text_value":"富士通株式会社データ＆セキュリティ研究所"},{"subitem_text_value":"富士通株式会社データ＆セキュリティ研究所"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Fujitsu Limited, Data and Security Research Laboratory","subitem_text_language":"en"},{"subitem_text_value":"Fujitsu Limited, Data and Security Research Laboratory","subitem_text_language":"en"},{"subitem_text_value":"Fujitsu Limited, Data and Security Research Laboratory","subitem_text_language":"en"},{"subitem_text_value":"Fujitsu Limited, Data and Security Research Laboratory","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/238959/files/IPSJ-DBS24179012.pdf","label":"IPSJ-DBS24179012.pdf"},"date":[{"dateType":"Available","dateValue":"2026-09-04"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DBS24179012.pdf","filesize":[{"value":"1.0 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"13"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"0d929031-a9a4-46cf-8e3b-b26d50a917b2","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"奥村, 泰久"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大木, 憲二"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"佐々木, 佑樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"北島, 信哉"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10112482","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":"2188-871X","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"インターネットから入手できる情報の中には，悪意のある偽情報が混ざっている可能性がある．この対策として，LLM を用いてもとの情報から真偽判定対象となるクレームを生成したうえで真偽判定を自動的に行う方法が研究されている．しかし，生成されたクレームのうち，情報が不十分で真偽判定できないクレームをどう除外するかという課題があった．そこで，真偽判定可能なクレームの基準を定めたうえで，LLM を用いて真偽判定できないクレームを判定する手法を提案する．性能評価の結果から，提案手法は従来手法と比べて判定精度が高いことを確認した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告データベースシステム（DBS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-09-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"12","bibliographicVolumeNumber":"2024-DBS-179"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":238959,"updated":"2025-01-19T08:26:16.087328+00:00","links":{}}