start-ver=1.4 cd-journal=joma no-vol= cd-vols= no-issue= article-no= start-page= end-page= dt-received= dt-revised= dt-accepted= dt-pub-year=2003 dt-pub=20030930 dt-online= en-article= kn-article= en-subject= kn-subject= en-title=多変量解析における変数選択とそのソフトウェア kn-title=Variable selection in multivariate methods and its software en-subtitle= kn-subtitle= en-abstract= kn-abstract= en-copyright= kn-copyright= en-aut-name=IizukaMasaya en-aut-sei=Iizuka en-aut-mei=Masaya kn-aut-name=飯塚誠也 kn-aut-sei=飯塚 kn-aut-mei=誠也 aut-affil-num=1 ORCID= affil-num=1 en-affil= kn-affil=岡山大学 END start-ver=1.4 cd-journal=joma no-vol=12 cd-vols= no-issue=1 article-no= start-page=29 end-page=40 dt-received= dt-revised= dt-accepted= dt-pub-year=2007 dt-pub=20070315 dt-online= en-article= kn-article= en-subject= kn-subject= en-title=Variable selection besed on global score estimation and its numerical investigation kn-title=合成変数の推定を利用した項目選択とその数値的検討 en-subtitle= kn-subtitle= en-abstract= kn-abstract=A variable selection method using global score estimation is proposed, which is applicable as a selection criterion in any multivariate method without external variables such as principal component analysis. This method selects a reasonable subset of variables so that the global scores, e.g. principal component scores, which are computed based on the selected variables, approximate the original global scores as well as possible in the context of the least squares. Three computational steps are proposed to estimate the scores according to how to satisfy the restriction that the estimated global scores are mutually uncorrelated. Three different examples are analyzed to demonstrate the performance and usefulness of the proposed method numerically, in which three steps are evaluated and the results obtained using four cost-saving selection procedures are compared. en-copyright= kn-copyright= en-aut-name=MoriYuichi en-aut-sei=Mori en-aut-mei=Yuichi kn-aut-name=森裕一 kn-aut-sei=森 kn-aut-mei=裕一 aut-affil-num=1 ORCID= en-aut-name=FuedaKaoru en-aut-sei=Fueda en-aut-mei=Kaoru kn-aut-name=笛田薫 kn-aut-sei=笛田 kn-aut-mei=薫 aut-affil-num=2 ORCID= en-aut-name=IizukaMasaya en-aut-sei=Iizuka en-aut-mei=Masaya kn-aut-name=飯塚誠也 kn-aut-sei=飯塚 kn-aut-mei=誠也 aut-affil-num=3 ORCID= affil-num=1 en-affil= kn-affil=岡山理科大学総合情報学部 affil-num=2 en-affil= kn-affil=岡山大学 affil-num=3 en-affil= kn-affil=岡山大学 en-keyword=principal components kn-keyword=principal components en-keyword=least square kn-keyword=least square en-keyword=orthogonalization kn-keyword=orthogonalization en-keyword=cost-saving selection kn-keyword=cost-saving selection END start-ver=1.4 cd-journal=joma no-vol=10 cd-vols= no-issue=1 article-no= start-page=49 end-page=56 dt-received= dt-revised= dt-accepted= dt-pub-year=2005 dt-pub=20050228 dt-online= en-article= kn-article= en-subject= kn-subject= en-title=Considering variable selection criteria in correspondence analysis kn-title=コレスポンデンス分析における変数選択規準の検討 en-subtitle= kn-subtitle= en-abstract= kn-abstract=Ordinary goodness of fit criteria in correspondence analysis are considered as variable selection criteria in case correspondence analysis which is one of multivariate methods without external variables can be applied. The goodness of fit criteria focused here are proportion of cumulative eigenvalues, proportion of cumulative squared-eigenvalues and proportion of cumulative off-diagonal fitness. Each criterion is applied to a couple of real data sets and evaluated with interpretation of the selection process and result (selected subset of variables). Four selection procedures such as backward elimination and forward-backward selection are also performed to compare with each other as well as with all possible selection procedure. These results illustrate that the criteria can be used as selection criteria to select a subset of variables in correspondence analysis and to assess categorical items (questions) in a survey (questionnaire). en-copyright= kn-copyright= en-aut-name=MoriYuichi en-aut-sei=Mori en-aut-mei=Yuichi kn-aut-name=森裕一 kn-aut-sei=森 kn-aut-mei=裕一 aut-affil-num=1 ORCID= en-aut-name=DuXiao Dong en-aut-sei=Du en-aut-mei=Xiao Dong kn-aut-name=杜暁東 kn-aut-sei=杜 kn-aut-mei=暁東 aut-affil-num=2 ORCID= en-aut-name=IizukaMasaya en-aut-sei=Iizuka en-aut-mei=Masaya kn-aut-name=飯塚誠也 kn-aut-sei=飯塚 kn-aut-mei=誠也 aut-affil-num=3 ORCID= affil-num=1 en-affil= kn-affil=岡山大学 affil-num=2 en-affil= kn-affil=岡山大学 affil-num=3 en-affil= kn-affil=岡山大学 END start-ver=1.4 cd-journal=joma no-vol=117 cd-vols= no-issue=207 article-no= start-page=47 end-page=51 dt-received= dt-revised= dt-accepted= dt-pub-year=2017 dt-pub=201709 dt-online= en-article= kn-article= en-subject= kn-subject= en-title=A Study of Extracting Related Documents for Essay Evaluation Modules kn-title=小論文採点支援のための関連文書取得法の考察 en-subtitle= kn-subtitle= en-abstract=We are developing an automatic Japanese essay-scoring system that is composed of 4 evaluation criteria, comprehensiveness, logical consistency, validity, spelling and grammar. In this paper, we discuss the most powerful approach to extract documents of Wikipedia that relates to the reference texts of the target essay theme for validity evaluation. The reason for using Wikipedia documents for evaluating validity of students’essays is that we assume that validity can be evaluated by the expanded discussions in Wikipedia documents that relates to the essay theme. Experimental results show that the skip-gram based word vector is the best approach to extract relating documents to reference texts among several keyword-based evaluation approaches. kn-abstract=本研究では，小論文採点システムにおいて必要となる小論文に関連した文書を取得する方法を開発した．本研究プロジェクトの自動採点の評価軸の1 つに「妥当性」がある．妥当性の評価手法として，小論文の内容がWikipediaの文書の内容と，どの程度一致しているかを基準に妥当性スコアを算出する方法を考えている．しかし，Wikipediaの文書は多様であり，小論文で取り上げていない議題に関する文書も多く存在する．そこで本論文では小論文ごとに適切な文書を取得する方法を提案する．いくつかの手法を試した結果，単語ベクトルを使用した方法が，関連した文書を獲得することができたことを報告する． en-copyright= kn-copyright= en-aut-name=MotojinKota en-aut-sei=Motojin en-aut-mei=Kota kn-aut-name=泉仁宏太 kn-aut-sei=泉仁 kn-aut-mei=宏太 aut-affil-num=1 ORCID= en-aut-name=TakeuchiKoichi en-aut-sei=Takeuchi en-aut-mei=Koichi kn-aut-name=竹内孔一 kn-aut-sei=竹内 kn-aut-mei=孔一 aut-affil-num=2 ORCID= en-aut-name=OhnoMasayuki en-aut-sei=Ohno en-aut-mei=Masayuki kn-aut-name=大野雅幸 kn-aut-sei=大野 kn-aut-mei=雅幸 aut-affil-num=3 ORCID= en-aut-name=TaguchiMasahiro en-aut-sei=Taguchi en-aut-mei=Masahiro kn-aut-name=田口雅弘 kn-aut-sei=田口 kn-aut-mei=雅弘 aut-affil-num=4 ORCID= en-aut-name=InadaYoshihiko en-aut-sei=Inada en-aut-mei=Yoshihiko kn-aut-name=稲田佳彦 kn-aut-sei=稲田 kn-aut-mei=佳彦 aut-affil-num=5 ORCID= en-aut-name=IizukaMasaya en-aut-sei=Iizuka en-aut-mei=Masaya kn-aut-name=飯塚誠也 kn-aut-sei=飯塚 kn-aut-mei=誠也 aut-affil-num=6 ORCID= en-aut-name=AboTatsuhiko en-aut-sei=Abo en-aut-mei=Tatsuhiko kn-aut-name=阿保達彦 kn-aut-sei=阿保 kn-aut-mei=達彦 aut-affil-num=7 ORCID= en-aut-name=UedaHitoshi en-aut-sei=Ueda en-aut-mei=Hitoshi kn-aut-name=上田均 kn-aut-sei=上田 kn-aut-mei=均 aut-affil-num=8 ORCID= affil-num=1 en-affil=Graduate School of Natural Science and Technology, Okayama University kn-affil=岡山大学大学院自然科学研究科 affil-num=2 en-affil=Graduate School of Natural Science and Technology, Okayama University kn-affil=岡山大学大学院自然科学研究科 affil-num=3 en-affil=Graduate School of Natural Science and Technology, Okayama University kn-affil=岡山大学大学院自然科学研究科 affil-num=4 en-affil=Graduate School of Natural Science and Technology, Okayama University kn-affil=岡山大学大学院自然科学研究科 affil-num=5 en-affil=Graduate School of Natural Science and Technology, Okayama University kn-affil=岡山大学大学院自然科学研究科 affil-num=6 en-affil=Graduate School of Natural Science and Technology, Okayama University kn-affil=岡山大学大学院自然科学研究科 affil-num=7 en-affil=Graduate School of Natural Science and Technology, Okayama University kn-affil=岡山大学大学院自然科学研究科 affil-num=8 en-affil=Graduate School of Natural Science and Technology, Okayama University kn-affil=岡山大学大学院自然科学研究科 en-keyword=小論文の自動採点 (Automatic scoring of answers of essay-writing tests) kn-keyword=小論文の自動採点 (Automatic scoring of answers of essay-writing tests) en-keyword=単語ベクトル (Word vector) kn-keyword=単語ベクトル (Word vector) en-keyword=Skip-gram kn-keyword=Skip-gram en-keyword=Wikipedia kn-keyword=Wikipedia END start-ver=1.4 cd-journal=joma no-vol=118 cd-vols= no-issue=355 article-no= start-page=103 end-page=108 dt-received= dt-revised= dt-accepted= dt-pub-year=2018 dt-pub=201812 dt-online= en-article= kn-article= en-subject= kn-subject= en-title=Proposing an Unsupervised Approach to Evaluate Essays Using IDF on Reference Data kn-title=参照データとidf を利用した事前採点不要な小論文評価手法 en-subtitle= kn-subtitle= en-abstract=In this paper, we describe an on-going study of developing an automatic essay-scoring system in Japanese. Essay scoring systems have already been developed and used mainly in English, while not many previous studies have been done on Japanese essay evaluations. Most of the methods and systems of automatic essay evaluation need not small number of previously human-graded essays for calibrating the parameter of regression functions or parameter of machine learning. The previous studies show the high performance for essay evaluation task, however, it must be not easy to assume large graded essays in, for example, actual tests or entrance examinations. Thus, we take a approach to evaluate Japanese essays without previously human-graded essays but with assuming reference data related to essay questions. The proposed method is a simple one, that is, evaluating the essays with co-occurrences with the reference data in their words or morphemes. In the method technical terms would be given high scores using neologd dictionary and idf values. Experimental results show that the proposed method works well in our developing Japanese mock trial writing tests. Key words automatic scoring of essays, human annotation, supporting kn-abstract=大学入試において2020 年から記述式問題が導入されることから記述式の問題を自動で採点する手法の開発が求められている．本論では，エッセイタイプの小論文課題を対象に，課題に関連する参照データとWikipedia 全文から作成したidf を利用した事前採点不要な自動採点手法を提案する．先行研究において，日本語小論文を対象とした自動採点では，多くの事前採点が必要となり，実際の数百人規模の試験では利用することが難しいと考えられる．そこで本研究では，事前採点が不要な小論文採点手法を提案する．また，小論文の模擬試験を実施して小論文データを構築する．構築した小論文データに対して採点手法を用い，実験を行い評価する．また小論文データの人手による採点に対しても評価を行う．評価実験の結果neologd 辞書を利用した形態素解析器を用いて， idf 値を利用した形態素の一致数が，人手の評価値と相関が高いことを示す． en-copyright= kn-copyright= en-aut-name=OhnoMasayuki en-aut-sei=Ohno en-aut-mei=Masayuki kn-aut-name=大野雅幸 kn-aut-sei=大野 kn-aut-mei=雅幸 aut-affil-num=1 ORCID= en-aut-name=TakeuchiKoichi en-aut-sei=Takeuchi en-aut-mei=Koichi kn-aut-name=竹内孔一 kn-aut-sei=竹内 kn-aut-mei=孔一 aut-affil-num=2 ORCID= en-aut-name=MotojinKota en-aut-sei=Motojin en-aut-mei=Kota kn-aut-name=泉仁宏太 kn-aut-sei=泉仁 kn-aut-mei=宏太 aut-affil-num=3 ORCID= en-aut-name=ObataYuya en-aut-sei=Obata en-aut-mei=Yuya kn-aut-name=小畑友也 kn-aut-sei=小畑 kn-aut-mei=友也 aut-affil-num=4 ORCID= en-aut-name=TaguchiMasahiro en-aut-sei=Taguchi en-aut-mei=Masahiro kn-aut-name=田口雅弘 kn-aut-sei=田口 kn-aut-mei=雅弘 aut-affil-num=5 ORCID= en-aut-name=InadaYoshihiko en-aut-sei=Inada en-aut-mei=Yoshihiko kn-aut-name=稲田佳彦 kn-aut-sei=稲田 kn-aut-mei=佳彦 aut-affil-num=6 ORCID= en-aut-name=IizukaMasaya en-aut-sei=Iizuka en-aut-mei=Masaya kn-aut-name=飯塚誠也 kn-aut-sei=飯塚 kn-aut-mei=誠也 aut-affil-num=7 ORCID= en-aut-name=AboTatsuhiko en-aut-sei=Abo en-aut-mei=Tatsuhiko kn-aut-name=阿保達彦 kn-aut-sei=阿保 kn-aut-mei=達彦 aut-affil-num=8 ORCID= en-aut-name=UedaHitoshi en-aut-sei=Ueda en-aut-mei=Hitoshi kn-aut-name=上田均 kn-aut-sei=上田 kn-aut-mei=均 aut-affil-num=9 ORCID= affil-num=1 en-affil=Graduate School of Natural Science and Technology, Okayama University kn-affil=岡山大学大学院自然科学研究科 affil-num=2 en-affil=Graduate School of Natural Science and Technology, Okayama University kn-affil=岡山大学大学院自然科学研究科 affil-num=3 en-affil=Graduate School of Natural Science and Technology, Okayama University kn-affil=岡山大学大学院自然科学研究科 affil-num=4 en-affil=Graduate School of Natural Science and Technology, Okayama University kn-affil=岡山大学大学院自然科学研究科 affil-num=5 en-affil=Graduate School of Humanities and Social Science, Okayama University kn-affil=岡山大学院社会文化科学研究科 affil-num=6 en-affil=Graduate School of Education, Okayama University kn-affil=岡山大学院教育学研究科 affil-num=7 en-affil=Institute for Education and Student Services, Okayama University kn-affil=岡山大学全学教育・学生支援機構 affil-num=8 en-affil=Institute for Education and Student Services, Okayama University kn-affil=岡山大学全学教育・学生支援機構 affil-num=9 en-affil=Institute for Education and Student Services, Okayama University kn-affil=岡山大学全学教育・学生支援機構 en-keyword=自動採点 (automatic scoring of essays) kn-keyword=自動採点 (automatic scoring of essays) en-keyword=アノテーション (human annotation) kn-keyword=アノテーション (human annotation) en-keyword=採点支援 (supporting system of essay evaluation) kn-keyword=採点支援 (supporting system of essay evaluation) en-keyword=idf kn-keyword=idf en-keyword=neologd kn-keyword=neologd END start-ver=1.4 cd-journal=joma no-vol=24 cd-vols= no-issue= article-no= start-page=368 end-page=371 dt-received= dt-revised= dt-accepted= dt-pub-year=2018 dt-pub=201803 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=小論文自動採点データ構築と理解力および妥当性評価手法の構築 en-subtitle= kn-subtitle= en-abstract= kn-abstract= en-copyright= kn-copyright= en-aut-name=OhnoMasayuki en-aut-sei=Ohno en-aut-mei=Masayuki kn-aut-name=大野雅幸 kn-aut-sei=大野 kn-aut-mei=雅幸 aut-affil-num=1 ORCID= en-aut-name= en-aut-sei= en-aut-mei= kn-aut-name=泉仁宏太 kn-aut-sei=泉仁 kn-aut-mei=宏太 aut-affil-num=2 ORCID= en-aut-name=TakeuchiKoichi en-aut-sei=Takeuchi en-aut-mei=Koichi kn-aut-name=竹内孔一 kn-aut-sei=竹内 kn-aut-mei=孔一 aut-affil-num=3 ORCID= en-aut-name= en-aut-sei= en-aut-mei= kn-aut-name=小畑友也 kn-aut-sei=小畑 kn-aut-mei=友也 aut-affil-num=4 ORCID= en-aut-name=TaguchiMasahiro en-aut-sei=Taguchi en-aut-mei=Masahiro kn-aut-name=田口雅弘 kn-aut-sei=田口 kn-aut-mei=雅弘 aut-affil-num=5 ORCID= en-aut-name=InadaYoshihiko en-aut-sei=Inada en-aut-mei=Yoshihiko kn-aut-name=稲田佳彦 kn-aut-sei=稲田 kn-aut-mei=佳彦 aut-affil-num=6 ORCID= en-aut-name=IizukaMasaya en-aut-sei=Iizuka en-aut-mei=Masaya kn-aut-name=飯塚誠也 kn-aut-sei=飯塚 kn-aut-mei=誠也 aut-affil-num=7 ORCID= en-aut-name= en-aut-sei= en-aut-mei= kn-aut-name=阿保達彦 kn-aut-sei=阿保 kn-aut-mei=達彦 aut-affil-num=8 ORCID= en-aut-name= en-aut-sei= en-aut-mei= kn-aut-name=上田均 kn-aut-sei=上田 kn-aut-mei=均 aut-affil-num=9 ORCID= affil-num=1 en-affil= kn-affil= affil-num=2 en-affil= kn-affil=岡山大学大学院自然科学研究科 affil-num=3 en-affil= kn-affil=岡山大学大学院自然科学研究科 affil-num=4 en-affil= kn-affil=岡山大学工学 affil-num=5 en-affil= kn-affil=岡山大学院社会文化科学研究 affil-num=6 en-affil= kn-affil=岡山大学院教育学研究科 affil-num=7 en-affil= kn-affil=岡山大学全学教育・学生支援機構 affil-num=8 en-affil= kn-affil=岡山大学大学院自然科学研究科 affil-num=9 en-affil= kn-affil=岡山大学大学院自然科学研究科 END start-ver=1.4 cd-journal=joma no-vol=23 cd-vols= no-issue= article-no= start-page=839 end-page=842 dt-received= dt-revised= dt-accepted= dt-pub-year=2017 dt-pub=201703 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=小論文の自動採点に向けたオープンな基本データの構築 および現段階での自動採点手法の評価 en-subtitle= kn-subtitle= en-abstract= kn-abstract= en-copyright= kn-copyright= en-aut-name=TakeuchiKoichi en-aut-sei=Takeuchi en-aut-mei=Koichi kn-aut-name=竹内孔一 kn-aut-sei=竹内 kn-aut-mei=孔一 aut-affil-num=1 ORCID= en-aut-name= en-aut-sei= en-aut-mei= kn-aut-name=大野雅幸 kn-aut-sei=大野 kn-aut-mei=雅幸 aut-affil-num=2 ORCID= en-aut-name= en-aut-sei= en-aut-mei= kn-aut-name=泉仁宏太 kn-aut-sei=泉仁 kn-aut-mei=宏太 aut-affil-num=3 ORCID= en-aut-name=TaguchiMasahiro en-aut-sei=Taguchi en-aut-mei=Masahiro kn-aut-name=田口雅弘 kn-aut-sei=田口 kn-aut-mei=雅弘 aut-affil-num=4 ORCID= en-aut-name=InadaYoshihiko en-aut-sei=Inada en-aut-mei=Yoshihiko kn-aut-name=稲田佳彦 kn-aut-sei=稲田 kn-aut-mei=佳彦 aut-affil-num=5 ORCID= en-aut-name=IizukaMasaya en-aut-sei=Iizuka en-aut-mei=Masaya kn-aut-name=飯塚誠也 kn-aut-sei=飯塚 kn-aut-mei=誠也 aut-affil-num=6 ORCID= en-aut-name=AboTatsuhiko en-aut-sei=Abo en-aut-mei=Tatsuhiko kn-aut-name=阿保達彦 kn-aut-sei=阿保 kn-aut-mei=達彦 aut-affil-num=7 ORCID= en-aut-name=UedaHitoshi en-aut-sei=Ueda en-aut-mei=Hitoshi kn-aut-name=上田均 kn-aut-sei=上田 kn-aut-mei=均 aut-affil-num=8 ORCID= affil-num=1 en-affil= kn-affil=岡山大学大学院自然科学研究科 affil-num=2 en-affil= kn-affil=岡山大学工学部 affil-num=3 en-affil= kn-affil=岡山大学工学部 affil-num=4 en-affil= kn-affil=岡山大学院社会文化科学研究科 affil-num=5 en-affil= kn-affil=岡山大学院教育学研究科 affil-num=6 en-affil= kn-affil=岡山大学全学教育・学生支援機構 affil-num=7 en-affil= kn-affil=岡山大学大学院自然科学研究科 affil-num=8 en-affil= kn-affil=岡山大学大学院自然科学研究科 END