{"id":80591,"updated":"2025-01-21T19:43:33.550731+00:00","links":{},"created":"2025-01-18T23:35:02.454307+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00080591","sets":["1:6573:6583"]},"path":["6583"],"owner":"13","recid":"80591","title":["不自然言語処理 -枠に収まらない「リアルな」言語処理-:6.Twitterからの情報抽出-感染症情報と被災文化財情報を例にして-"],"pubdate":{"attribute_name":"公開日","attribute_value":"2012-02-15"},"_buckets":{"deposit":"896ec71d-5546-45a8-b4db-28e7b1aef888"},"_deposit":{"id":"80591","pid":{"type":"depid","value":"80591","revision_id":0},"owners":[13],"status":"published","created_by":13},"item_title":"不自然言語処理 -枠に収まらない「リアルな」言語処理-:6.Twitterからの情報抽出-感染症情報と被災文化財情報を例にして-","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"不自然言語処理 -枠に収まらない「リアルな」言語処理-:6.Twitterからの情報抽出-感染症情報と被災文化財情報を例にして-"},{"subitem_title":"Robust NLP for Real-world Data : 6. Information Extraction from Twitter - Epidemic Surveillance and Damaged Cultural Assets - ","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"特集","subitem_subject_scheme":"Other"}]},"item_type_id":"1","publish_date":"2012-02-15","item_1_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京大学"},{"subitem_text_value":"東京工業大学"}]},"item_1_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"The Univ. of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"Tokyo Institute of Technology","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/80591/files/IPSJ-MGN530309.pdf"},"date":[{"dateType":"Available","dateValue":"2014-02-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MGN530309.pdf","filesize":[{"value":"1.4 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"0","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"f8f4a724-732a-4430-89b1-c249e5f34311","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2012 by the Information Processing Society of Japan"}]},"item_1_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"荒牧, 英治"},{"creatorName":"橋本, 泰一"}],"nameIdentifiers":[{}]}]},"item_1_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Eiji, ARAMAKI","creatorNameLang":"en"},{"creatorName":"Taiichi, HASHIMOTO","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_1_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00116625","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":"article"}]},"item_1_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年のマイクロブログの普及とともに,そこから有益な情報を抽出する需要が高まっている.ここでは,マイクロブログの先駆者的なサービスであるTwitterを例にして,インフルエンザや花粉症といった疾患病の患者数を予測する情報抽出システムと東日本大震災により被災した文化財の情報抽出について解説する.両システムともに,特定のキーワードを含むツイートの数を数え上げるだけでなく,機械学習による文書分類器を活用することにより,日常的な文章からより正確な情報抽出に取り組んでいる.","subitem_description_type":"Other"}]},"item_1_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"240","bibliographic_titles":[{"bibliographic_title":"情報処理"}],"bibliographicPageStart":"236","bibliographicIssueDates":{"bibliographicIssueDate":"2012-02-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"3","bibliographicVolumeNumber":"53"}]},"relation_version_is_last":true,"weko_creator_id":"13"}}