{"links":{},"id":175052,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00175052","sets":["581:8417:8428"]},"path":["8428"],"owner":"11","recid":"175052","title":["ソーシャルネットワークにおける共通の友人に着目した実世界イベント分類手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2016-10-15"},"_buckets":{"deposit":"f50b3419-9a56-4fb7-a5b4-8525a422b801"},"_deposit":{"id":"175052","pid":{"type":"depid","value":"175052","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"ソーシャルネットワークにおける共通の友人に着目した実世界イベント分類手法","author_link":["363985","363976","363986","363983","363978","363977","363981","363973","363975","363988","363979","363987","363980","363984","363974","363982"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ソーシャルネットワークにおける共通の友人に着目した実世界イベント分類手法"},{"subitem_title":"Classifying Urban Events by Analyzing Common Friends in Location-based Social Network","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[特集：ユビキタスコンピューティングシステム（Ⅴ）] ソーシャルネットワーク，位置情報サービス，実世界イベント検知","subitem_subject_scheme":"Other"}]},"item_type_id":"2","publish_date":"2016-10-15","item_2_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"慶應義塾大学大学院政策メディア研究科"},{"subitem_text_value":"慶應義塾大学大学院政策メディア研究科"},{"subitem_text_value":"慶應義塾大学大学院政策メディア研究科"},{"subitem_text_value":"慶應義塾大学大学院政策メディア研究科／慶應義塾大学環境情報学部"},{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"慶應義塾大学大学院政策メディア研究科／慶應義塾大学環境情報学部"}]},"item_2_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Media and Governance, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Media and Governance, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Media and Governance, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Media and Governance, Keio University / Faculty of Environment and Information Studies, Keio University","subitem_text_language":"en"},{"subitem_text_value":"NTT DoCoMo, Inc.","subitem_text_language":"en"},{"subitem_text_value":"NTT DoCoMo, Inc.","subitem_text_language":"en"},{"subitem_text_value":"NTT DoCoMo, Inc.","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Media and Governance, Keio University / Faculty of Environment and Information Studies, Keio 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/175052/files/IPSJ-JNL5710012.pdf","label":"IPSJ-JNL5710012.pdf"},"date":[{"dateType":"Available","dateValue":"2018-10-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-JNL5710012.pdf","filesize":[{"value":"5.7 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":"8"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"f2d358b6-c917-4189-a9cb-c6b72b4aee31","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2016 by the Information Processing Society of Japan"}]},"item_2_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"佐藤, 翔野"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"米澤, 拓郎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"河野, 慎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中澤, 仁"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"川崎, 仁嗣"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"太田, 賢"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"稲村, 浩"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"徳田, 英幸"}],"nameIdentifiers":[{}]}]},"item_2_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shoya, Sato","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takuro, Yonezawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Makoto, Kawano","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Jin, Nakazawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hitoshi, Kawasaki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Ken, Oota","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hiroshi, Inamura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hideyuki, Tokuda","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，ソーシャルネットワーク上の情報を使い実世界のイベントを検出・分類する研究がさかんに行われている．既存の研究ではソーシャルネットワーク上に投稿された発言のテキスト解析が主であり，発言にイベントに関する内容が含まれていないと解析が困難であるという問題が存在する．本研究では，Twitter上の位置情報付き発言を用いて，ある空間に存在するTwitterユーザの興味を発言のテキスト解析を行うことなく抽出し，それに基づいた実世界イベントの検出と分類を試みる．提案手法では，空間内のユーザ群の「共通の友人」を分析し，その友人の属性情報をWikipediaを参照して解析することにより，イベントの属性を抽出する．提案手法により自動抽出されたイベント分類と，27名の被験者によるイベント分類とを比較した結果，趣味性の高いイベントに関して高い類似性を持ったイベント分類が可能であることが分かった．","subitem_description_type":"Other"}]},"item_2_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Recently, many researchers focus to detect and classify urban events by analyzing information on social network. Previous work mainly use text analysis of users' posts on social networks for detecting urban events; however, this approach has a limitation that users' posts must mention event information. We develop a new method to detect and classify urban events by extracting users' interests from location-based social network information without using text analysis. Our method analyses common friends in users who exist in the area of on-going events, and extract common friends' attributes from related Wikipedia information. We designed and implemented the proposed method, and carried out experiment for evaluating our method. Our experimental result shows that our method can classify events, where participants have similar interests, with high similarity by compared with ground truth created by questionnaire.","subitem_description_type":"Other"}]},"item_2_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"2235","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌"}],"bibliographicPageStart":"2222","bibliographicIssueDates":{"bibliographicIssueDate":"2016-10-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"10","bibliographicVolumeNumber":"57"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"created":"2025-01-19T00:45:06.299542+00:00","updated":"2025-01-20T06:21:06.096302+00:00"}