{"updated":"2025-01-22T10:32:14.756378+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00044311","sets":["1164:3925:3926:3928"]},"path":["3928"],"owner":"1","recid":"44311","title":["頻出パータン木を利用した安全な相関ルール発見手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2008-07-17"},"_buckets":{"deposit":"b55349d0-5734-4b94-82ef-716e6c791747"},"_deposit":{"id":"44311","pid":{"type":"depid","value":"44311","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"頻出パータン木を利用した安全な相関ルール発見手法","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"頻出パータン木を利用した安全な相関ルール発見手法"},{"subitem_title":"A Secure Association Rules Mining Scheme Based on Frequent-Pattern Tree","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2008-07-17","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"九州大学大学院システム情報科学府"},{"subitem_text_value":"九州大学大学院システム情報科学研究院"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Computer Science and Communication Engineering, Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Department of Computer Science and Communication Engineering, Kyushu University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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/44311/files/IPSJ-CSEC08042044.pdf"},"date":[{"dateType":"Available","dateValue":"2010-07-17"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CSEC08042044.pdf","filesize":[{"value":"235.0 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":"30"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"e4487ca1-7b0f-4276-bb6d-d9476a29d5b6","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":"蘇春華"},{"creatorName":"櫻井, 幸一"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Chunhua, Su","creatorNameLang":"en"},{"creatorName":"Kouichi, Sakurai","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11235941","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":"Many government organizations and companies want to share their documents in a similar theme to get the joint benefits. Textual document clustering is a powerful data mining technique to analyze the large amount of documents and structure large sets of text or hypertext documents. While doing the document clustering in the distributed environment  it may involve the users' privacy of their own document. In this paper  we propose a framework to do the privacy-preserving text mining among the users under the distributed environment: multiple parties  each having their private documents  want to collaboratively execute agglomerative document clustering without disclosing their private contents to any other parties.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Many government organizations and companies want to share their documents in a similar theme to get the joint benefits. Textual document clustering is a powerful data mining technique to analyze the large amount of documents and structure large sets of text or hypertext documents. While doing the document clustering in the distributed environment, it may involve the users' privacy of their own document. In this paper, we propose a framework to do the privacy-preserving text mining among the users under the distributed environment: multiple parties, each having their private documents, want to collaboratively execute agglomerative document clustering without disclosing their private contents to any other parties.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"315","bibliographic_titles":[{"bibliographic_title":"情報処理学会研究報告コンピュータセキュリティ（CSEC）"}],"bibliographicPageStart":"311","bibliographicIssueDates":{"bibliographicIssueDate":"2008-07-17","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"71(2008-CSEC-042)","bibliographicVolumeNumber":"2008"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"created":"2025-01-18T23:10:31.128583+00:00","id":44311,"links":{}}