{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00123369","sets":["6504:8032:8036"]},"path":["8036"],"owner":"1","recid":"123369","title":["量的な判断常識を備えた人工知能 : 量的な属性の自動獲得手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"1993-03-01"},"_buckets":{"deposit":"17fd31ff-52c0-41f4-bb12-91bfda824a21"},"_deposit":{"id":"123369","pid":{"type":"depid","value":"123369","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"量的な判断常識を備えた人工知能 : 量的な属性の自動獲得手法","author_link":[],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"量的な判断常識を備えた人工知能 : 量的な属性の自動獲得手法"},{"subitem_title":"Artificial Intelligence with Quantitative Common Sense : Automatic Knowledge Acquisition of Quantitative Attributes","subitem_title_language":"en"}]},"item_type_id":"22","publish_date":"1993-03-01","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":"NTT情報通信網研究所"},{"subitem_text_value":"NTT情報通信網研究所"},{"subitem_text_value":"NTT情報通信網研究所"},{"subitem_text_value":"NTT情報通信網研究所"}]},"item_22_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"NTT Network Information Systems Laboratories","subitem_text_language":"en"},{"subitem_text_value":"NTT Network Information Systems Laboratories","subitem_text_language":"en"},{"subitem_text_value":"NTT Network Information Systems Laboratories","subitem_text_language":"en"},{"subitem_text_value":"NTT Network Information Systems Laboratories","subitem_text_language":"en"}]},"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/123369/files/KJ00001337201.pdf"},"date":[{"dateType":"Available","dateValue":"1993-03-01"}],"format":"application/pdf","filename":"KJ00001337201.pdf","filesize":[{"value":"226.9 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"2f26fe0c-6d1e-4658-81da-337d8ec3250b","displaytype":"detail","licensetype":"license_note"}]},"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":"人間の持つ柔軟な理解や判断能力を計算機に持たせることを目的として,量的な判断常識を備えた人工知能の研究を行なっている。量的な判断常識は,(1)対象を表す概念(対象概念),(2)量の尺度を表す概念(重属性),(3)比較の程度を表す概念(比較概念),(4)比較の程度を修飾する概念などから構成される。量的な判断常識の構築において,対象概念および対象概念と量属性との関係(対量関係)は大規模となるため,対象概念として既存シソーラスを用い,テキストから抽出された対量関係を対象概念と量属性間に張ることを試みた。しかし,テキスト中に含まれる対量関係が非常に少ないために,大規模な対量関係構築の見通しが得られなかった。そこで,既存シソーラスを利用し,抽出された対量関係を継承することにより対量関係の導出を考える。しかし,既存シソーラスは必ずしも量の観点から階層化されていないので,量の観点から妥当な階層だけを使った対象概念の階層化により対量関係を継承させる手法を提案する。本手法は,対量関係の抽出,対象概念の階層化,対量関係の整理の手順からなる。また,本手法を辞書の例文に適用した結果を示す。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"44","bibliographic_titles":[{"bibliographic_title":"全国大会講演論文集"}],"bibliographicPageStart":"43","bibliographicIssueDates":{"bibliographicIssueDate":"1993-03-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"人工知能及び認知科学","bibliographicVolumeNumber":"第46回"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"updated":"2025-01-21T02:59:07.911207+00:00","created":"2025-01-19T00:03:27.429664+00:00","links":{},"id":123369}