{"id":9386,"updated":"2025-01-23T03:26:22.395339+00:00","links":{},"created":"2025-01-18T22:44:37.107663+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00009386","sets":["581:586:588"]},"path":["588"],"owner":"1","recid":"9386","title":["大域的情報を用いた日本語固有表現認識"],"pubdate":{"attribute_name":"公開日","attribute_value":"2008-11-15"},"_buckets":{"deposit":"2652196f-c881-4c9f-9f0c-7fecdfb00899"},"_deposit":{"id":"9386","pid":{"type":"depid","value":"9386","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"大域的情報を用いた日本語固有表現認識","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"大域的情報を用いた日本語固有表現認識"},{"subitem_title":"Japanese Named Entity Recognition Using Non-local Information","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"一般論文","subitem_subject_scheme":"Other"}]},"item_type_id":"2","publish_date":"2008-11-15","item_2_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京大学大学院情報理工学系研究科 日本学術振興会特別研究員DC"},{"subitem_text_value":"京都大学大学院情報学研究科"}]},"item_2_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Information Science and Technology, the University of Tokyo,Research Fellow of the Japan Society for the Promotion of Science","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Infomatics, Kyoto 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/9386/files/IPSJ-JNL4911006.pdf"},"date":[{"dateType":"Available","dateValue":"2010-11-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-JNL4911006.pdf","filesize":[{"value":"200.3 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":"8"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"e43fed57-a2e0-4338-a765-b02783146dd2","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2008 by the Information Processing Society of Japan"}]},"item_2_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"笹野, 遼平"},{"creatorName":"黒橋, 禎夫"}],"nameIdentifiers":[{}]}]},"item_2_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Ryohei, Sasano","creatorNameLang":"en"},{"creatorName":"Sadao, Kurohashi","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":"本稿では大域的情報を用いた日本語固有表現認識手法を提案する．提案する手法では，SVMを用いた固有表現認識手法を基とし，構造的な解析などから得られる大域的な情報として，先行文における同一形態素の解析結果，共参照関係にある表現の解析結果，係り先から得られる情報，固有表現情報を付与した格フレームを用いた格解析から得られる情報の4つの情報を新たに導入する．CRL固有表現データ（5分割交差検定），IREXテストセット，および，ウェブテキストに固有表現を付与したデータを用いた評価実験の結果，従来手法より高い精度が得られ，手法の有効性が確認された．","subitem_description_type":"Other"}]},"item_2_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"This paper presents an approach that uses non-local information for Japanese named entity recognition (NER). Our NER system is based on Support Vector Machine (SVM), and utilizes four types of non-local information: cache features, coreference relations, syntactic features and case-frame features, which are obtained from structural analyses. We evaluated our approach on CRL NE data and obtained a higher F-measure than existing approaches that do not use non-local information. We also conducted experiments on IREX NE data and an NE-annotated web corpus and confirmed that non-local information improves the performance of NER.","subitem_description_type":"Other"}]},"item_2_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"3776","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌"}],"bibliographicPageStart":"3765","bibliographicIssueDates":{"bibliographicIssueDate":"2008-11-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"11","bibliographicVolumeNumber":"49"}]},"relation_version_is_last":true,"item_2_alternative_title_2":{"attribute_name":"その他タイトル","attribute_value_mlt":[{"subitem_alternative_title":"自然言語"}]},"weko_creator_id":"1"}}