{"created":"2025-01-18T23:02:33.217801+00:00","updated":"2025-01-22T15:30:27.373010+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00033807","sets":["1164:2822:2823:2825"]},"path":["2825"],"owner":"1","recid":"33807","title":["決定木の比較を利用したコンセプトドリフトの解析"],"pubdate":{"attribute_name":"公開日","attribute_value":"2008-06-12"},"_buckets":{"deposit":"b962ce1d-e7c6-4503-b459-3c41fb5c4d38"},"_deposit":{"id":"33807","pid":{"type":"depid","value":"33807","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"決定木の比較を利用したコンセプトドリフトの解析","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"決定木の比較を利用したコンセプトドリフトの解析"},{"subitem_title":"Comparison Method for Decision Trees to Analyze Concept Drift","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2008-06-12","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"日本アイ・ビー・エム株式会社"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"IBM Japan,Ltd.","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/33807/files/IPSJ-EMB08009001.pdf"},"date":[{"dateType":"Available","dateValue":"2010-06-12"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-EMB08009001.pdf","filesize":[{"value":"1.3 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":"42"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"f5ae6a80-686b-4ada-aeb3-c050366861bf","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2008 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"久保, 晴信"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Harunobu, Kubo","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12149313","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_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"多くの分野において，時系列に変化するストリーミングデータの分析は重要な研究テーマとなってる．例えば，購買履歴動向の分析において購買動向のトレンドと，その変化を捕らえることは，企業にとって死活問題となっている．ストリーミングデータマイニングの分野では分別器を用いて時系列データの変化の検出が行われている．そのような変化のことをコンセプトドリフトと呼んでいる．本研究では，分別器として決定木を用いる，なぜならば決定木には豊かな説明能力があるからである．つまり決定木の変化はコンセプトドリフトの発生を意味していると考えられる．一般的には決定木の比較は難しい問題である．そこで我々は決定木の比較方法を提案し，コンセプトドリフトの発生を決定木の比較により検出する．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In various applications, it is an important research theme to get to know the feature of streaming data which are changing in time. For example, in analysis of purchase history information, it is very important to catch the continuity of a purchase trend and its change, and it forces a life-and-death problem for the company. In stream data mining, a change of the feature of time series data is detected by using classifiers. Such change is called a concept drift. The change of decision trees are considered as the concept drift. We use decision tree as classifiers because it has rich explanation ability of the streaming data. In general to compare decision trees is difficult problem. We introduce the method to compare two decision trees and detect a concept drift based on the comparison method of decision trees.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"情報処理学会研究報告組込みシステム（EMB）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2008-06-12","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"55(2008-EMB-009)","bibliographicVolumeNumber":"2008"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"id":33807,"links":{}}