{"links":{},"id":195445,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00195445","sets":["934:989:9698:9699"]},"path":["9699"],"owner":"44499","recid":"195445","title":["Word2Vecにおける加算型単語ベクトルの効果と応用"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-03-15"},"_buckets":{"deposit":"160278c3-154e-4de8-ad42-3ce96744eded"},"_deposit":{"id":"195445","pid":{"type":"depid","value":"195445","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Word2Vecにおける加算型単語ベクトルの効果と応用","author_link":["465378","465381","465380","465377","465379","465376"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Word2Vecにおける加算型単語ベクトルの効果と応用"},{"subitem_title":"Effect and Application of Additional Vector in Word2Vec","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[オリジナル論文] Word2Vec，分散表現，加算ベクトル，アナロジータスク，文書分類","subitem_subject_scheme":"Other"}]},"item_type_id":"3","publish_date":"2019-03-15","item_3_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"名古屋大学大学院工学研究科"},{"subitem_text_value":"名古屋大学大学院工学研究科"},{"subitem_text_value":"名古屋大学大学院工学研究科"}]},"item_3_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Engineering, Nagoya University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Engineering, Nagoya University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Engineering, Nagoya 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/195445/files/IPSJ-TOM1201004.pdf","label":"IPSJ-TOM1201004.pdf"},"date":[{"dateType":"Available","dateValue":"2021-03-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-TOM1201004.pdf","filesize":[{"value":"702.5 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":"39ccabc7-941a-40f7-b232-b09413ae264d","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2019 by the Information Processing Society of Japan"}]},"item_3_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"内田, 脩斗"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"吉川, 大弘"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"古橋, 武"}],"nameIdentifiers":[{}]}]},"item_3_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shuto, Uchida","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tomohiro, Yoshikawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takeshi, Furuhashi","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_3_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11464803","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_3_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7780","subitem_source_identifier_type":"ISSN"}]},"item_3_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Word2Vecは，単語の分散表現を獲得する最も一般的な手法の1つであり，自然言語処理分野における構文解析や文書分類などに適用した研究も数多く報告され始め，その有用性が示唆されている．この手法では，2種類の分散表現が生成されるが，従来は一般的に，その一方のみを利用して単語の分散表現としている．一方で，それらを加算した単語ベクトルW ADDを利用することによる，意味関係性能の向上が報告されている．しかし，その際示された実験では，同時にパラメータのチューニングも行っており，性能向上の要因が不明瞭なものとなっている．また，W ADDを実タスクに応用した際に，精度への貢献が期待できるかどうかについては明示されていない．そこで本論文では，アナロジータスクにおいて分散表現の意味関係性能を評価し，観測的事実に基づいてW ADDの精度向上原因の解析を行う．加えて，文書分類タスクにおいて，各分散表現による分類精度の比較・検討を行い，その有用性について報告する．","subitem_description_type":"Other"}]},"item_3_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Word2Vec is one of the most common methods for acquiring a distributed representation of words. In the field of natural language processing, many studies applying Word2Vec to syntactic analysis and document classification have been reported and its usefulness is suggested. In this method, two kinds of distributed representations are generated, and generally, only one of them is actually used. On the other hand, the improvement of semantic relation performance has been reported by using the word vector W ADD generated by adding two kinds of distributed representations. However, in the experiment, other parameters are tuned at the same time, and factors of the improvement are not clear. Moreover, it is unknown whether the improvement of accuracy can be expected when W ADD is applied to real tasks. Therefore, in this study, we evaluate the semantic relation performance of distributed representations with analogy tasks and analyze the cause of improvement of W ADD based on observational facts. In addition, we conduct a document classification task using each distributed representation and report its usefulness.","subitem_description_type":"Other"}]},"item_3_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"31","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌数理モデル化と応用（TOM）"}],"bibliographicPageStart":"23","bibliographicIssueDates":{"bibliographicIssueDate":"2019-03-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"12"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:00:22.554948+00:00","updated":"2025-01-19T23:06:40.110462+00:00"}