{"created":"2023-07-27T07:53:34.941227+00:00","id":29400,"links":{},"metadata":{"_buckets":{"deposit":"785d8b32-45db-4587-90c0-3ff36748a39b"},"_deposit":{"created_by":21,"id":"29400","owners":[21],"pid":{"revision_id":0,"type":"depid","value":"29400"},"status":"published"},"_oai":{"id":"oai:doshisha.repo.nii.ac.jp:00029400","sets":["4251:8138:8139:8140:9229","8:3372:3847:9228"]},"author_link":["30843","30844","30845"],"item_1693811493084":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_1694490770713":{"attribute_name":"権利者情報","attribute_value_mlt":[{"nameIdentifiers":[{"nameIdentifier":"DA18202107","nameIdentifierScheme":"AID"}],"rightHolderNames":[{"rightHolderLanguage":"ja","rightHolderName":"同志社大学ハリス理化学研究所"},{"rightHolderLanguage":"en","rightHolderName":"Harris Science Research Institute of Doshisha University"}]}]},"item_1_biblio_info_14":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2023-01-31","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"4","bibliographicPageEnd":"214","bibliographicPageStart":"209","bibliographicVolumeNumber":"63","bibliographic_titles":[{"bibliographic_title":"同志社大学ハリス理化学研究報告","bibliographic_titleLang":"ja"},{"bibliographic_title":"The Harris science review of Doshisha University","bibliographic_titleLang":"en"}]}]},"item_1_description_12":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"サービス開発者にとって，利用者からのフィードバックや意見を得ることは機能の改善に重要である．本研究報告では，サービス利用者のツイートからアイディアを抽出するアプローチを提案する．提案手法は，ツイート収集，テキスト特徴抽出，可視化から構成され，いずれも簡便な方法で実現されている．実際の有名なチャットサービスを対象とした実験では，機械学習ベースによる置き換えと比較することで，提案手法の有効性を示す．また，開発した可視化インタフェースにより実験結果を定性的に分析する．","subitem_description_language":"ja","subitem_description_type":"Abstract"},{"subitem_description":"Service developers are constantly working to improve their services. Although opinions and feedback from users are important for improving their services, conducting an interview is time consuming. Thus, this paper proposes an approach for extracting ideas from service users' tweets. The proposed method consists of tweet collection, textual feature extraction, and visualization, which are easy to implement. In experiments targeting three famous chat services, we demonstrated the effectiveness of the proposed method compared with machine learning methods. 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夏希 / 同志社大学大学院理工学研究科情報工学専攻"},{"subitem_text_language":"ja","subitem_text_value":"長尾, 浩良 / 同志社大学理工学部研究補助員"},{"subitem_text_language":"ja","subitem_text_value":"桂井, 麻里衣 / 同志社大学理工学部准教授"}]},"item_1_text_9":{"attribute_name":"著者所属（英）","attribute_value_mlt":[{"subitem_text_language":"en","subitem_text_value":"Hashimoto, Natsuki / Department of Information and Computer Science, Graduate School of Science and Engineering, Doshisha University"},{"subitem_text_language":"en","subitem_text_value":"Nagao, Hiroyoshi / Department of Intelligent Information Engineering and Sciences, Faculty of Science and Engineering, Doshisha University"},{"subitem_text_language":"en","subitem_text_value":"Katsurai, Marie / Department of Intelligent Information Engineering and Sciences, Faculty of Science and Engineering, Doshisha University"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open 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