{"updated":"2025-01-23T02:16:22.926795+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00011349","sets":["581:651:663"]},"path":["663"],"owner":"1","recid":"11349","title":["サポートベクターマシンによる適合性フィードバックを用いた情報検索"],"pubdate":{"attribute_name":"公開日","attribute_value":"2003-01-15"},"_buckets":{"deposit":"7ae2ef14-6b6b-47f7-b975-0e4ea73fc574"},"_deposit":{"id":"11349","pid":{"type":"depid","value":"11349","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"サポートベクターマシンによる適合性フィードバックを用いた情報検索","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"サポートベクターマシンによる適合性フィードバックを用いた情報検索"},{"subitem_title":"Relevance Feedback Using Support Vector Machine for Information Retrieval","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"論文","subitem_subject_scheme":"Other"}]},"item_type_id":"2","publish_date":"2003-01-15","item_2_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"徳島大学工学部"},{"subitem_text_value":"徳島大学工学部"},{"subitem_text_value":"徳島大学工学部"},{"subitem_text_value":"徳島大学高度情報化基盤センター"}]},"item_2_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Faculty of Engineering, Tokushima University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Engineering, Tokushima University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Engineering, Tokushima University","subitem_text_language":"en"},{"subitem_text_value":"Center for Advanced Information Technology, Tokushima University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/11349/files/IPSJ-JNL4401007.pdf"},"date":[{"dateType":"Available","dateValue":"2005-01-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-JNL4401007.pdf","filesize":[{"value":"189.8 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":"8"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"d8c82ded-b843-42d8-8767-bcc332667349","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2003 by the Information Processing Society of Japan"}]},"item_2_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"柘植, 覚"},{"creatorName":"獅々堀正幹"},{"creatorName":"黒岩, 眞吾"},{"creatorName":"北, 研二"}],"nameIdentifiers":[{}]}]},"item_2_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Satoru, Tsuge","creatorNameLang":"en"},{"creatorName":"Masami, Shishibori","creatorNameLang":"en"},{"creatorName":"Shingo, Kuroiwa","creatorNameLang":"en"},{"creatorName":"Kenji, Kita","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_2_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00116647","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_2_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7764","subitem_source_identifier_type":"ISSN"}]},"item_2_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年のインターネット技術の発展により，World Wide Web（WWW）を代表とする個人で扱えるオンラインテキストデータの量が増加している．それにともない，莫大なテキストデータ中から必要な情報を検索する機会も増え，情報検索に関する研究への関心が高まっている．情報検索システムとして，検索対象文書と検索質問を多次元ベクトルで表現するベクトル空間モデル（VSM: Vector Space Model）が広く使用されている．VSMを用いた検索システムの精度を改善する手法の1つとして，適合性フィードバック手法（Relevance Feedback）が提案されている．この手法は，VSMを用いた1次検索結果に対し，利用者が適合・不適合の判断を行いその情報をシステムにフィードバックし，再検索を行うことで検索精度を向上させている．本論文では，この利用者からのフィードバック情報を検索対象文書全体の適合・不適合の判別に用いた．判別を行う識別器として，従来手法より，判別の能力が高く，汎化性に優れたサポートベクターマシン（SVM: Support Vector Machine）を用いた．このフィードバック手法をサポートベクターマシンによる適合性フィードバックとして本論文で提案する．日本語テストコレクション（BMIR-J2）を用いた類似文書検索実験において，提案手法は従来手法と比較し，利用者が判断し，システムにフィードバックされる文書数が50の場合，24.0%の検索精度改善を得ることが可能であった．","subitem_description_type":"Other"}]},"item_2_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"With the rapid growth of online information, e.g., the World Wide Web(WWW), a large collection of full-text documents is available andopportunity for getting a useful piece of information is increased.Information Retrieval (IR) is now becoming one of the most importantissues for handling large text data.Relevance feedback is a technique that improves retrieval performancebased on relevance judgments from the user. Here, we propose therelevance feedback method using Support Vector Machine (SVM).Experiment results on Japanese test collection BMIR-J2 show that theproposed method is useful feedback method comparing to theconventional feedback method. Especially, the proposed method improvedthe performance of IR system.","subitem_description_type":"Other"}]},"item_2_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"67","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌"}],"bibliographicPageStart":"59","bibliographicIssueDates":{"bibliographicIssueDate":"2003-01-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"44"}]},"relation_version_is_last":true,"item_2_alternative_title_2":{"attribute_name":"その他タイトル","attribute_value_mlt":[{"subitem_alternative_title":"情報検索"}]},"weko_creator_id":"1"},"created":"2025-01-18T22:46:00.245742+00:00","id":11349,"links":{}}