{"id":145886,"updated":"2025-01-20T18:11:07.261077+00:00","links":{},"created":"2025-01-19T00:21:27.685357+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00145886","sets":["1164:1165:8308:8366"]},"path":["8366"],"owner":"11","recid":"145886","title":["分析者による試行錯誤を促進するデータ分析ツールの提案と試作"],"pubdate":{"attribute_name":"公開日","attribute_value":"2015-11-19"},"_buckets":{"deposit":"d849b71e-e315-4fd6-9824-e0fa95d444d1"},"_deposit":{"id":"145886","pid":{"type":"depid","value":"145886","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"分析者による試行錯誤を促進するデータ分析ツールの提案と試作","author_link":["225971","225969","225968","225970"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"分析者による試行錯誤を促進するデータ分析ツールの提案と試作"},{"subitem_title":"Designing and developing an interactive data minig tool for rapid repeating trials","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"機械学習","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2015-11-19","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"日本電気株式会社"},{"subitem_text_value":"日本電気株式会社"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"NEC Corporation","subitem_text_language":"en"},{"subitem_text_value":"NEC Corporation","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/145886/files/IPSJ-DBS15162005.pdf","label":"IPSJ-DBS15162005.pdf"},"date":[{"dateType":"Available","dateValue":"2017-11-19"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DBS15162005.pdf","filesize":[{"value":"1.1 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":"13"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"fb489889-f59c-436a-a5b7-8a1dfb0e278c","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2015 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"加藤, 大志"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"三木, 清一"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Daishi, Kato","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Miki, Kiyokazu","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10112482","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":"2188-871X","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"大規模データを分析して規則や知識を発見するデータマイニングが注目されている．データマイニングではしばしば機械学習の手法を用いるが，学習パラメータの入力や学習結果の評価において分析者の役割が重要となる．よりよい分析結果を得るには分析者が試行錯誤を重ねることが重要で，そのためには分析実行から結果評価のサイクルを速く回すことが求められる．本稿では，試行錯誤を促進するために，学習に計算時間がかかる場合でも実行中の途中結果を可視化できるデータ分析ツールを提案する．機械学習の EM アルゴリズムを用いた一つの手法を対象に，提案を具体化したプロトタイプシステムを開発した．本プロトタイプシステムでは，アルゴリズムの途中結果を確認しつつアルゴリズムの終了を待つことなく分析を再実行できるようになり，試行錯誤の促進が期待できることが分かった．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Data mining has got attention for finding rules and knowledge out of big data. Machine learning technique is often used in data mining, and the role of data analysts is important to design input parameters and evaluate output results. To get better results, trials and errors by analysts are important. Hence, a method for repeating design/evaluation cycles rapidly is desired. We propose an interactive data mining tool which allows to visualize intermediate results from a time-consuming algorithm We developed a prototype tool with an EM algorithm based machine learning algorithm. With this tool, users can observe the intermediate results and stop the algorithm for another trial if necessary.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告データベースシステム（DBS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2015-11-19","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"5","bibliographicVolumeNumber":"2015-DBS-162"}]},"relation_version_is_last":true,"weko_creator_id":"11"}}