{"updated":"2025-01-19T15:48:22.222636+00:00","links":{},"created":"2025-01-19T01:17:06.225152+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00216559","sets":["1164:2735:10865:10866"]},"path":["10866"],"owner":"44499","recid":"216559","title":["グラフ畳み込みネットワークによる推理小説の犯人推定"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-02-24"},"_buckets":{"deposit":"4293897e-5012-4537-9ed9-aa0f42bcf1ce"},"_deposit":{"id":"216559","pid":{"type":"depid","value":"216559","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"グラフ畳み込みネットワークによる推理小説の犯人推定","author_link":["559066","559069","559068","559067"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"グラフ畳み込みネットワークによる推理小説の犯人推定"},{"subitem_title":"A Criminal Detection of Mystery Novel Using the Graph Convolutional Network","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2022-02-24","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京都市大学大学院総合理工学研究科"},{"subitem_text_value":"東京都市大学大学院総合理工学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Integrative Science and Engineering, Tokyo City University Graduate School","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Integrative Science and Engineering, Tokyo City University Graduate School","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/216559/files/IPSJ-MPS22137013.pdf","label":"IPSJ-MPS22137013.pdf"},"date":[{"dateType":"Available","dateValue":"2024-02-24"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS22137013.pdf","filesize":[{"value":"404.3 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"17"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"392fb263-5124-4aef-8e70-9b328d93037c","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"勝島, 修平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"穴田, 一"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shuhei, Katsushima","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hajime, Anada","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10505667","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":"2188-8833","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，機械学習への社会的な期待が高まっている一方，専門家でも推論過程に対して説明を与えられないことが問題となっている．そんな中，解釈可能性を題材とした推論を行うコンテスト「ナレッジグラフ推論チャレンジ」が開催された．既存研究では，単語の意味を学習するために埋め込みに基づいた手法が提案されているが，小説上の場所，時間，対象物などの同時性を考慮できていない．本研究では，Graph Convolutional Network (GCN) を用いてグラフの構造関係をそのまま学習し，重要となるグラフの関係を Layer-wise Relevance Propagation (LRP) によって明らかにすることによって犯人推定を行う手法を提案する．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"The interpretability problem, where even experts cannot explain the reasoning process of machine learning, has garnered considerable attention recently. Knowledge Graph Reasoning Challenge 2018, a contest concentrating on interpretability, was conducted in Tokyo. A previous study proposed a method based on word embedding to understand the meaning of the word in the novel. However, the method resulted in ignoring the flow of events. In this study, the graph structure is learned by Graph Convolutional Network, and we explain the important connections on graph by layer-wise relevance propagation.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"2","bibliographic_titles":[{"bibliographic_title":"研究報告数理モデル化と問題解決（MPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-02-24","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"13","bibliographicVolumeNumber":"2022-MPS-137"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":216559}