{"id":70136,"updated":"2025-01-21T23:35:13.759275+00:00","links":{},"created":"2025-01-18T23:29:26.083936+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00070136","sets":["934:1022:6082:6148"]},"path":["6148"],"owner":"11","recid":"70136","title":["内部および外部重みを考慮した頻出部分グラフマイニング"],"pubdate":{"attribute_name":"公開日","attribute_value":"2010-06-24"},"_buckets":{"deposit":"8e140ba8-cbeb-42ba-9b54-2e40a4edd0aa"},"_deposit":{"id":"70136","pid":{"type":"depid","value":"70136","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"内部および外部重みを考慮した頻出部分グラフマイニング","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"内部および外部重みを考慮した頻出部分グラフマイニング"},{"subitem_title":"Weighted Frequent Subgraph Mining in Weighted Graph Databases","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"研究論文","subitem_subject_scheme":"Other"}]},"item_type_id":"3","publish_date":"2010-06-24","item_3_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"神戸大学工学部"},{"subitem_text_value":"大阪大学サイバーメディアセンター"},{"subitem_text_value":"神戸大学大学院システム情報学研究科"}]},"item_3_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Faculty of Engineering, Kobe University","subitem_text_language":"en"},{"subitem_text_value":"Cybermedia Center, Osaka University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of System Informatics, Kobe University","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/70136/files/IPSJ-TOD0302002.pdf"},"date":[{"dateType":"Available","dateValue":"2012-06-24"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-TOD0302002.pdf","filesize":[{"value":"546.1 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":"13"},{"tax":["include_tax"],"price":"0","billingrole":"39"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"d0cbbd1c-363c-4f11-ac34-50d047859da9","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2010 by the Information Processing Society of Japan"}]},"item_3_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"信田, 正樹"},{"creatorName":"尾崎, 知伸"},{"creatorName":"大川, 剛直"}],"nameIdentifiers":[{}]}]},"item_3_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Masaki, Shinoda","creatorNameLang":"en"},{"creatorName":"Tomonobu, Ozaki","creatorNameLang":"en"},{"creatorName":"Takenao, Ohkawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_3_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11464847","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_3_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7799","subitem_source_identifier_type":"ISSN"}]},"item_3_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，グラフデータの増大にともない，そこから何らかの意味のあるパターンや情報を発見するグラフマイニング手法に関する研究がさかんに行われている．本論文では，グラフマイニングの 1 つの発展として，グラフ自身およびグラフの各構成要素に対し，その重要性や信頼性，意義などを表す重みが付与された，外部および内部の重み付きグラフからのパターン発見について議論する．具体的には，重みに着目したパターンの重要性尺度として，一般重み付き頻度 （GWF），および制約付き重み付き頻度 （CWF） の 2 つを考案するとともに，GWF および CWF に関して高い重要性を示す部分グラフを発見する効率的なアルゴリズム，GWF-mine および CWF-mine をそれぞれ提案する．","subitem_description_type":"Other"}]},"item_3_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Recently, graph-structured data is becoming popular in many application domains, and several studies on graph mining have been performed for discovering useful knowledge from graph databases. In this paper, in order to realize more precise knowledge discovery in graph databases, we focus on pattern discovery problems from externally and internally weighted graphs where external weight represents a degree of importance and reliability of a graph itself and internal weight reflects utility and significance of each component in a graph. By using external and internal weights, we propose two importance measures named (1) general weighted frequency (GWF) and (2) external weighted frequency under the constraint of internal weight (CWF), and develop efficient algorithms GWF-mine and CWF-mine for extracting subgraphs having high value of these measures. Experimental results by using synthetic and real world datasets show the effectiveness of the proposed framework.","subitem_description_type":"Other"}]},"item_3_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"12","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌データベース（TOD）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2010-06-24","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"3"}]},"relation_version_is_last":true,"weko_creator_id":"11"}}