{"updated":"2025-01-20T05:37:25.537942+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00177071","sets":["1164:3500:9054:9055"]},"path":["9055"],"owner":"11","recid":"177071","title":["専門家記事と機械学習に基づくWebニュースからの日経平均株価予測"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-02-03"},"_buckets":{"deposit":"709ffbc1-0de0-4eeb-b50d-4fd6befb8abb"},"_deposit":{"id":"177071","pid":{"type":"depid","value":"177071","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"専門家記事と機械学習に基づくWebニュースからの日経平均株価予測","author_link":["375017","375014","375016","375015"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"専門家記事と機械学習に基づくWebニュースからの日経平均株価予測"},{"subitem_title":"Stock market prediction from Web news using expert articles and machine learning","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"エキスパートからの知識獲得","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2017-02-03","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"九州工業大学大学院情報工学府先端情報工学専攻"},{"subitem_text_value":"九州工業大学大学院情報工学府先端情報工学専攻"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Kyushu Institute of Technology, Graduate School of Computer Science and Systems Engineering","subitem_text_language":"en"},{"subitem_text_value":"Kyushu Institute of Technology, Graduate School of Computer Science and Systems Engineering","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/177071/files/IPSJ-IFAT17124004.pdf","label":"IPSJ-IFAT17124004.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-IFAT17124004.pdf","filesize":[{"value":"2.0 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"39"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"3219a2f5-b348-48a2-94ca-8321e5c56d73","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2017 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"一瀬, 航"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"嶋田, 和孝"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Ko, Ichinose","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kazutaka, Shimada","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10114171","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":"2188-8884","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，機械学習を用いたテキストマイニング手法によって，テキスト情報と市場変動の関係性を発見し，市場分析に応用する研究が増えている．また，Web ニュースは企業の株価に少なからず影響を与えており，世に存在する個人投資家がこのニュース記事を参考にしていると考えると，Web ニュースから未来の株価が予測できる可能性がある．そこで本論文では，Web ニュースを対象とし，より多くの投資家が市場の分析に用いていると考えられる指標である日経平均株価の予測を目的とする．テキストを用いた金融予測では膨大なテキスト情報を用いて機械学習を行うことが一般的である．しかし，投資家は市場に影響を与える多様な情報を自ら取捨選択し，独自の着眼点にしたがって市場の分析を行っている．本研究では，この着眼点，つまり，分析にどのような情報が必要なのかという知識を専門家の分析記事から抽出し，これにより機械学習の精度が向上するかの検証と新素性の提案を行う．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"The market analysis is one of the important tasks for text mining. Many researchers have proposed methods using text information for analyzing the market. In this situation. Web news has an important role to predict stock prices. In this paper, we propose a method to predict the Nikkei Stock Average, which is one of the most important stock market indexes. We extract viewpoints for analyzing web-news from analysis's articles of an expert and apply the viewpoints and a machine learning technique into the method. Then, we classify the next day into \"UP\" or \"DOWN\" by using the articles of a day. The experimental result shows the effectiveness of extracting viewpoints from expert articles.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告情報基礎とアクセス技術（IFAT）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2017-02-03","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"4","bibliographicVolumeNumber":"2017-IFAT-124"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"created":"2025-01-19T00:46:39.502892+00:00","id":177071,"links":{}}