{"id":48853,"updated":"2025-01-22T08:18:06.133560+00:00","links":{},"created":"2025-01-18T23:14:00.093107+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00048853","sets":["1164:4179:4250:4253"]},"path":["4253"],"owner":"1","recid":"48853","title":["スパースな学習データにおけるPCFGの確率パラメタの推定法"],"pubdate":{"attribute_name":"公開日","attribute_value":"1998-07-23"},"_buckets":{"deposit":"ef02cae0-07b8-48af-9b60-0627f98d5dce"},"_deposit":{"id":"48853","pid":{"type":"depid","value":"48853","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"スパースな学習データにおけるPCFGの確率パラメタの推定法","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"スパースな学習データにおけるPCFGの確率パラメタの推定法"},{"subitem_title":"A parameter Estimation of a Probabilistic Context Free Grammar on a Sparse Sample","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"1998-07-23","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"九州大学大学院システム情報科学研究科"},{"subitem_text_value":"九州大学大学院システム情報科学研究科"},{}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Information Science and Electrical Engineering, Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science and Electrical Engineering, Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science and Electrical Engineering, Kyushu University","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/48853/files/IPSJ-NL98126006.pdf"},"date":[{"dateType":"Available","dateValue":"2000-07-23"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-NL98126006.pdf","filesize":[{"value":"721.2 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":"23"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"98533737-949a-419c-b7a1-82bce0950143","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 1998 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"冨浦洋一"},{"creatorName":"ニシダタケシ"},{"creatorName":"日高達"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yoichi, Tomiura","creatorNameLang":"en"},{"creatorName":"Takeshi, Nishida","creatorNameLang":"en"},{"creatorName":"Toru, Hitaka","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10115061","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"自然言語文の統語構造の曖昧さを絞り込む手法として，統語範疇を意味カテゴリで細分化することにより，係り受け制約を生成規則として表現した確率文脈自由文法を用いる解析が考えられる．しかし，詳細な係り受け制約を記述すると，生成規則数が膨大となり，最尤推定による高信頼度のパラメタ推定値を得るために必要な学習データを収集することが困難となる．本稿では，このような確率文法のパラメタ推定法として，ほとんどの場合に最尤推定量より平均的に誤差が小さく，学習データが十分でない場合により有効となる推定量を提案し，英語の前置詞句の係り先の判定を対象として行なった評価実験について報告する．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"We can disambiguate syntactic structures of a sentence based on a Probabilistic Context Free Grammar (PCFG), where syntactic categories are subdivided semantically so that dependency constraints are expressed in the productioon rules. But to describe dependency constraints in detail causes an explosion of the number of production rules, which makes it difficult to collect enough size of sample to get a reliable maximum likelihood estimate of parameters in the PCFG. This paper proposes a new estimator of parameters in the PCFG and show the result of an experiment in disambiguation of English prepositional phrase attachment. The mean error of the proposed estimator is practically smaller than the one of the maximum likelihood estimator, and this tendency is more conspicuous on a small size of sample.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"46","bibliographic_titles":[{"bibliographic_title":"情報処理学会研究報告自然言語処理（NL）"}],"bibliographicPageStart":"39","bibliographicIssueDates":{"bibliographicIssueDate":"1998-07-23","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"63(1998-NL-126)","bibliographicVolumeNumber":"1998"}]},"relation_version_is_last":true,"weko_creator_id":"1"}}