{"links":{},"id":188663,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00188663","sets":["6504:9465:9481"]},"path":["9481"],"owner":"6748","recid":"188663","title":["語意類似度を用いた指示詞の照応解析システムAnasysD"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-03-13"},"_buckets":{"deposit":"90cf2d8e-97d5-4b99-a8e4-0fe55c5b51df"},"_deposit":{"id":"188663","pid":{"type":"depid","value":"188663","revision_id":0},"owners":[6748],"status":"published","created_by":6748},"item_title":"語意類似度を用いた指示詞の照応解析システムAnasysD","author_link":["428195","428193","428194"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"語意類似度を用いた指示詞の照応解析システムAnasysD"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人工知能と認知科学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2018-03-13","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"青学大"},{"subitem_text_value":"青学大"},{"subitem_text_value":"青学大"}]},"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/188663/files/IPSJ-Z80-6P-06.pdf","label":"IPSJ-Z80-6P-06.pdf"},"date":[{"dateType":"Available","dateValue":"2018-05-07"}],"format":"application/pdf","filename":"IPSJ-Z80-6P-06.pdf","filesize":[{"value":"1.4 MB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"1363d077-008e-4dae-a1fa-577390928ef0","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2018 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"西念, 星宝"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"谷津, 元樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"原田, 実"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"対話や質問応答において、解析対象文に指示詞が含まれる場合、その照応先の同定精度が重要である。本研究では、意味解析システムSAGEによって得られる解析結果を元にして、語意に基づく素性を用いた照応解析システムAnasysyDを開発する。照応詞を名詞形態指示詞、連体詞形態指示詞(物型)、連体詞形態指示詞(事象型)、人称代名詞の4つに分類した上で、素性に先行詞候補が持つ、指示詞との距離や概念類似度、などの情報を使用し、これらの値からナイーブベイズ法を用いた確率論的手法で先行詞らしさのスコアを算出し、スコアの最も値が高いものを先行詞としている。合わせて、学習法としてランダムフォレスト、深層学習、トーナメントモデルなどを用いた比較も報告する。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"304","bibliographic_titles":[{"bibliographic_title":"第80回全国大会講演論文集"}],"bibliographicPageStart":"303","bibliographicIssueDates":{"bibliographicIssueDate":"2018-03-13","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2018"}]},"relation_version_is_last":true,"weko_creator_id":"6748"},"created":"2025-01-19T00:54:47.406015+00:00","updated":"2025-01-20T02:00:21.425754+00:00"}