{"created":"2025-01-19T01:00:03.990364+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00195049","sets":["1164:4402:9710:9736"]},"path":["9736"],"owner":"44499","recid":"195049","title":["自動ファシリテーターのIBIS構造抽出のための系列ラベリング"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-03-11"},"_buckets":{"deposit":"b6d4fb9a-f694-484a-9bbb-cdc4e6ed8e53"},"_deposit":{"id":"195049","pid":{"type":"depid","value":"195049","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"自動ファシリテーターのIBIS構造抽出のための系列ラベリング","author_link":["463411","463414","463412","463415","463410","463416","463413"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"自動ファシリテーターのIBIS構造抽出のための系列ラベリング"},{"subitem_title":"Sequence labeling for extraction of Issue-Based Information System Structures for Automated Facilitator Agent","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"合意形成とエージェント","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2019-03-11","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"名古屋工業大学"},{"subitem_text_value":"名古屋工業大学"},{"subitem_text_value":"名古屋工業大学"},{"subitem_text_value":"名古屋工業大学"},{"subitem_text_value":"名古屋工業大学"},{"subitem_text_value":"名古屋工業大学"},{"subitem_text_value":"名古屋工業大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Nagoya Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Nagoya Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Nagoya Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Nagoya Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Nagoya Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Nagoya Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Nagoya Institute of Technology","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/195049/files/IPSJ-ICS19195008.pdf","label":"IPSJ-ICS19195008.pdf"},"date":[{"dateType":"Available","dateValue":"2021-03-11"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ICS19195008.pdf","filesize":[{"value":"1.5 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":"25"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"98492248-4776-4ef5-915f-7c3b3e298e09","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2019 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"芳野, 魁"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"西田, 智裕"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山口, 直子"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"柴田, 大地"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鈴木, 祥太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"平石, 健太郎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"伊藤, 孝行"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11135936","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":"2188-885X","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本稿では，多人数参加型議論のテキストから議論構造を抽出するためのモデルを提示する．多様な意見を開かれた形で集めることができるため，オンライン議論が注目されている．議論においてファシリテーターは重要な役割を果たしているが議論の規模が大きくなるに連れて人間のファシリテーターが把握するのは時間的及び情報量的に困難となる．従ってファシリテーターを自動化することが求められているが，自動化のためには議論構造の把握が不可欠である．そこで私達は議論中の発言を入力として時系列順に入力し，新たに投稿された発言に含まれている議論的な要素を取り出すニューラルネットワークモデルを提案する．評価実験では大規模合意形成システム D-Agree で行われた議論のアノテーション済みテキストデータに対して議論構造の抽出を行った．実験の結果，提案するモデルが良い性能を獲得できることを示した．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In this paper, we propose a model for parsing discussion structures in online discussions that are composed of a set of submissions posted by multiple participants. Since various opinions can be gathered in an opened form, online discussions have attracted attention. While facilitators play an important role in discussion, it becomes difficult for human facilitators to grasp whole discussion as time goes and information volume as the scale of discussion grows. In this regard, we set creating automated software agents that can function as facilitators in a facilitator-based online discussion system as our goal. Towards this end, it is essential to understand the discussion structures. We extracted the discussion structures based on issue-based information system (IBIS) from the online discussions that consist of submissions posted by various participants. In addition, we proposed a new model for extraction. The proposed extraction model receives a number of submissions, including the newly posted submissions in online discussions along with their time sequences as inputs. Then, the proposed model predicts the probability that each morpheme in the newly posted submissions belongs to each IBIS category. The proposed model passes the summarized information of past submissions to help understanding the context of the discussion. We evaluated the proposed model using the discussion texts that are collected from the online discussions created in intelligent crowd decision-making support system, D-Agree. The evaluation results demonstrated that the proposed model can extract the correct information with high precision.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告知能システム（ICS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2019-03-11","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"8","bibliographicVolumeNumber":"2019-ICS-195"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":195049,"updated":"2025-01-19T23:14:14.838494+00:00","links":{}}