{"id":82117,"updated":"2025-01-21T19:08:50.808034+00:00","links":{},"created":"2025-01-18T23:36:04.054406+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00082117","sets":["1164:2735:6701:6774"]},"path":["6774"],"owner":"11","recid":"82117","title":["人間乱数によるSOMを利用した個人識別の可能性"],"pubdate":{"attribute_name":"公開日","attribute_value":"2012-05-10"},"_buckets":{"deposit":"0798ad3d-dce5-4966-b0c9-27a0f39ee9db"},"_deposit":{"id":"82117","pid":{"type":"depid","value":"82117","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"人間乱数によるSOMを利用した個人識別の可能性","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"人間乱数によるSOMを利用した個人識別の可能性"},{"subitem_title":"Possibility of the Personal Identification Using SOM by a Human Random Generation","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2012-05-10","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"鳥取大学大学院工学研究科エレクトロニクス専攻"},{"subitem_text_value":"鳥取大学大学院工学研究科エレクトロニクス専攻"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Tottori University, Graduate School of Engineering, Department of Information and Electronics","subitem_text_language":"en"},{"subitem_text_value":"Tottori University, Graduate School of Engineering, Department of Information and Electronics","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/82117/files/IPSJ-MPS12088014.pdf"},"date":[{"dateType":"Available","dateValue":"2014-05-10"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS12088014.pdf","filesize":[{"value":"1.8 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":"17"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"ded7fdbb-a04b-4d64-b785-492077c5140b","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2012 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"田中, 侑希"},{"creatorName":"田中, 美栄子"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yuuki, Tanaka","creatorNameLang":"en"},{"creatorName":"Mieko, Tanaka-Yamawaki","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10505667","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":"人が生成した乱数列のことを人間乱数と呼び，被験者の体調や生成方法によって数列の特徴が変化することが知られている．人間乱数を個人で識別するためには乱数列に個人の癖（特徴）が反映される生成方法を考える必要がある．本研究では乱数列に個人の癖が反映される生成方法として，乱数生成時の思考度合が異なる2種類のデータを採取し比較を行うことで両者の特徴を捉えることを目的とした．採取したデータを用いて様々な指標を計算した結果，直感的に生成した場合と熟考して生成した場合とで明確に差が現れず，どちらもある程度個人の癖が反映されることがわかった．そこで8種類の特徴量となる指標を用いてSOMによる個人分類実験を行ったところ，熟考データに比べて直感データの方が個人を分類する上で，より適していると思われる結果となった．また，特徴量のうち，データ採取時の被験者の行動パターンを反映するものが重要であったことから，データ列の解析だけでなく被験者の行動を指標として取り入れることによって個人分類の可能性が高まることがわかった．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"The human random numbers are the random sequences generated by human, which are known to reflect the subjects condition and also to depend on the methods of data takings. In order to identify individuals based on such data, we need a good experimental method in which the feature of individual subjects is reflected in the data as much as possible. We aimed in this work to compare two methods of data taking, the ‘intuitive’ generation and the ‘deliberate’ generation. We found that the difference between the results of the two types of data generation is rather small, and both reflect the features of individual to some extent. The result of SOM learning based on eight indicators, however, shows that the ‘intuitive’ data are more suitable for individual identification than the ‘deliberate’ data. We also found that the two indicators out of the eight that are related to the subjects habitual pattern play an important role in the SOM classification, indicating the importance of taking account of subjects habitual pattern as well as the features exhibited in data sequences.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告数理モデル化と問題解決（MPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2012-05-10","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"14","bibliographicVolumeNumber":"2012-MPS-88"}]},"relation_version_is_last":true,"weko_creator_id":"11"}}