{"created":"2025-01-19T01:33:51.792820+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00232792","sets":["1164:2735:11468:11517"]},"path":["11517"],"owner":"44499","recid":"232792","title":["感情分析における文書間距離の重み付けの検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-02-29"},"_buckets":{"deposit":"4e697966-0063-48d7-9042-83a89183ceba"},"_deposit":{"id":"232792","pid":{"type":"depid","value":"232792","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"感情分析における文書間距離の重み付けの検討","author_link":["631018","631019","631016","631017"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"感情分析における文書間距離の重み付けの検討"},{"subitem_title":"Consideration of the Weighting Method of Document Similarity Measures in Sentiment Analysis","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2024-02-29","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"阪南大学"},{"subitem_text_value":"大阪公立大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Hannan University","subitem_text_language":"en"},{"subitem_text_value":"Osaka Metropolitan University","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/232792/files/IPSJ-MPS24147009.pdf","label":"IPSJ-MPS24147009.pdf"},"date":[{"dateType":"Available","dateValue":"2026-03-01"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS24147009.pdf","filesize":[{"value":"579.4 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":"7716508b-24aa-4e16-bb1c-af729c93fccd","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":"松田, 健"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中島, 智晴"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Takeshi, Matsuda","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tomoharu, Nakashima","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":"現在の自然言語処理の技術は Transformer をベースとした高性能なモデルが複数提案されており，高度な文章の自動生成も実現可能になっている．Transformer をベースとするモデルの多くは一定の文脈の読み取りが可能であると考えられているものの，ある背景から生成された文章に対してその文脈を分析したり，ポジティブ/ネガティブのような感情分析を実現することについてはまだ課題があると考えられる．本研究では，文章や単語間の距離を測るいくつかの手法の課題を整理し，改善する方法について検討する．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Recently, several high-performance models based on Transformer have been proposed in natural language processing technology, and it is now possible to automatically generate advanced sentences. Although it can be considered that many models based on Transformer could read a certain amount of context, there is a case where it is difficult to analyze the context of sentences generated from a certain background or perform sentiment analysis such as positive/negative. In this study, we will organize the problems of several methods for measuring the distance between sentences and words and consider their improved methods.","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":"2024-02-29","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"9","bibliographicVolumeNumber":"2024-MPS-147"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"links":{},"id":232792,"updated":"2025-01-19T10:19:12.907233+00:00"}