{"id":95859,"updated":"2025-01-21T13:32:47.387103+00:00","links":{},"created":"2025-01-18T23:42:51.040171+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00095859","sets":["1164:4179:6969:7304"]},"path":["7304"],"owner":"11","recid":"95859","title":["適合性フィードバックにおけるユーザ負荷軽減手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2013-11-07"},"_buckets":{"deposit":"454b98a2-8830-4bb0-8dc1-fd0378c56824"},"_deposit":{"id":"95859","pid":{"type":"depid","value":"95859","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"適合性フィードバックにおけるユーザ負荷軽減手法","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"適合性フィードバックにおけるユーザ負荷軽減手法"},{"subitem_title":"Reducing the Effort of the User on Relevance Feedback","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"文章分析","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2013-11-07","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"千葉大学大学院融合科学研究科"},{"subitem_text_value":"千葉大学大学院融合科学研究科"},{"subitem_text_value":"千葉大学大学院融合科学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Chiba University, Graduate School of Advanced Integration Science","subitem_text_language":"en"},{"subitem_text_value":"Chiba University, Graduate School of Advanced Integration Science","subitem_text_language":"en"},{"subitem_text_value":"Chiba University, Graduate School of Advanced Integration Science","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/95859/files/IPSJ-NL13214003.pdf"},"date":[{"dateType":"Available","dateValue":"2015-11-07"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-NL13214003.pdf","filesize":[{"value":"687.4 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":"23"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"e78703e5-6748-4c68-be38-e5f0bb8c8d30","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2013 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"金子, 弘明"},{"creatorName":"梅澤, 猛"},{"creatorName":"大澤, 範高"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hiroaki, Kaneko","creatorNameLang":"en"},{"creatorName":"Takeshi, Umezawa","creatorNameLang":"en"},{"creatorName":"Noritaka, Osawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10115061","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":"情報検索において初期検索結果に対するユーザ評価を基に有用な文献を収集・絞り込みを行う適合性フィードバック手法は，ユーザに特別な検索技術や知識を要さず再検索を容易にする．しかし，適合・不適合の判別精度がフィードバック数と相関を持つため，高い効果を得るにはユーザに検索結果を多くの文献を閲覧・評価する労力を要する．そこで本論文ではユーザの労力を軽減するために，少量のフィードバックから機械学習手法を用いて疑似的なフィードバックを得る手法を検討する．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Relevance feedback in Information retrieval can be used to refine search queries based on user feedback to results returned by initial query and collect relevance documents easier even if a user has no specialized knowledge. Since, precision of relevance feedback is correlated with the number of feedback, highly effective relevance feedback usually needs for the user to give much feedback and then to review many documents. This paper, investigates a method which get pseudo feedback from machine learning trained on a little feedback.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告自然言語処理（NL）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2013-11-07","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"3","bibliographicVolumeNumber":"2013-NL-214"}]},"relation_version_is_last":true,"weko_creator_id":"11"}}