{"links":{},"id":2004386,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:02004386","sets":["6164:6165:6522:1752235746399"]},"path":["1752235746399"],"owner":"11","recid":"2004386","title":["生成AIを活用したITシステム障害対応ナレッジ作成および検索方式の検討と評価"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2025-09-09"},"_buckets":{"deposit":"c26604ee-d128-4158-9f45-16c9f9167132"},"_deposit":{"id":"2004386","pid":{"type":"depid","value":"2004386","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"生成AIを活用したITシステム障害対応ナレッジ作成および検索方式の検討と評価","author_link":[],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"生成AIを活用したITシステム障害対応ナレッジ作成および検索方式の検討と評価","subitem_title_language":"ja"},{"subitem_title":"Study and Evaluation of Knowledge Creation and Search Methods for IT System Incident Response Utilizing Generative AI","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"企業視点・開発プロセスの実証的分析","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2025-09-09","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"日立製作所"},{"subitem_text_value":"日立製作所"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Hitachi, Ltd.","subitem_text_language":"en"},{"subitem_text_value":"Hitachi, Ltd.","subitem_text_language":"en"}]},"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/2004386/files/IPSJ-SES2025016.pdf","label":"IPSJ-SES2025016.pdf"},"date":[{"dateType":"Available","dateValue":"2027-09-09"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SES2025016.pdf","filesize":[{"value":"1.3 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":"12"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"29aa41b5-64ac-4343-9bd6-8e2dd9f513db","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2025 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"和田,清美"}]},{"creatorNames":[{"creatorName":"増田,峰義"}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Kiyomi Wada","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Mineyoshi Masuda","creatorNameLang":"en"}]}]},"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_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"インシデント管理（システムやサービスに発生した問題を迅速かつ効果的に解決するためのプロセス）において，生成AIを活用して，インシデント対応履歴から障害対応ナレッジとしてFAQ（症状と問題・解決策）を自動作成してナレッジDBに登録できるようになったが，類似のFAQが複数作成・登録されるため，障害時に類似症状のFAQが複数見つかり検索精度が低下していた．そこで，FAQを作成しナレッジDBに登録する時に重複を排除し，検索時はFAQを絞り込むために症状を背景で分類したツリー表示を提案した．オープンデータを用いて，類似症状で異なる問題・解決策を判別することで重複を排除し，ナレッジDB検索結果から症状を背景で分類したツリー表示によりFAQを絞り込むことができた．これより，障害対応後の迅速なFAQ作成とナレッジDB登録，障害時の効率的なナレッジDB検索が実現できる見通しを得た．","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In the context of incident management—a process aimed at resolving issues arising in systems or services both promptly and effectively—we have developed a method utilizing generative AI to automatically generate FAQs (comprising symptoms, underlying issues, and corresponding solutions) from historical incident response records, and to register them into a knowledge database. However, this approach resulted in the creation and registration of multiple similar FAQs, which in turn degraded search accuracy during incident response due to the presence of redundant entries for similar symptoms. To address this limitation, we propose a method that eliminates redundancy at the time of FAQ generation and registration, and enhances search efficiency by organizing FAQs into a hierarchical tree structure based on the background context of the symptoms. By leveraging open data, we succeeded in distinguishing cases with similar symptoms but differing root causes and solutions, thereby suppressing duplication. Furthermore, the classification tree enabled refined filtering of FAQs by contextual symptom categorization during search. This approach shows promise for realizing both rapid FAQ generation and systematic registration into the knowledge database following incident resolution, as well as efficient and accurate retrieval of relevant knowledge during subsequent incident handling.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"85","bibliographic_titles":[{"bibliographic_title":"ソフトウェアエンジニアリングシンポジウム2025論文集"}],"bibliographicPageStart":"79","bibliographicIssueDates":{"bibliographicIssueDate":"2025-09-09","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2025"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"created":"2025-09-05T07:47:32.436855+00:00","updated":"2025-09-05T07:47:36.379112+00:00"}