言語処理学会Acta Medica Okayama232017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839842ENKoichiTakeuchiMasahiroTaguchiYoshihikoInadaMasayaIizukaTatsuhikoAboHitoshiUedaNo potential conflict of interest relevant to this article was reported.言語処理学会Acta Medica Okayama242018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368371ENMasayukiOhnoKoichiTakeuchiMasahiroTaguchiYoshihikoInadaMasayaIizukaNo potential conflict of interest relevant to this article was reported.電子情報通信学会Acta Medica Okayama091356851183552018参照データとidf を利用した事前採点不要な小論文評価手法103108ENMasayukiOhnoGraduate School of Natural Science and Technology, Okayama UniversityKoichiTakeuchiGraduate School of Natural Science and Technology, Okayama UniversityKotaMotojinGraduate School of Natural Science and Technology, Okayama UniversityYuyaObataGraduate School of Natural Science and Technology, Okayama UniversityMasahiroTaguchiGraduate School of Humanities and Social Science, Okayama UniversityYoshihikoInadaGraduate School of Education, Okayama UniversityMasayaIizukaInstitute for Education and Student Services, Okayama UniversityTatsuhikoAboInstitute for Education and Student Services, Okayama UniversityHitoshiUedaInstitute for Education and Student Services, Okayama University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．No potential conflict of interest relevant to this article was reported.電子情報通信学会Acta Medica Okayama091356851172072017小論文採点支援のための関連文書取得法の考察4751ENKotaMotojinGraduate School of Natural Science and Technology, Okayama UniversityKoichiTakeuchiGraduate School of Natural Science and Technology, Okayama UniversityMasayukiOhnoGraduate School of Natural Science and Technology, Okayama UniversityMasahiroTaguchiGraduate School of Natural Science and Technology, Okayama UniversityYoshihikoInadaGraduate School of Natural Science and Technology, Okayama UniversityMasayaIizukaGraduate School of Natural Science and Technology, Okayama UniversityTatsuhikoAboGraduate School of Natural Science and Technology, Okayama UniversityHitoshiUedaGraduate School of Natural Science and Technology, Okayama University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．No potential conflict of interest relevant to this article was reported.岡山大学環境理工学部Acta Medica Okayama1341-90991012005コレスポンデンス分析における変数選択規準の検討4956ENYuichiMoriXiao DongDuMasayaIizuka10.18926/fest/11489Ordinary 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).No potential conflict of interest relevant to this article was reported.岡山大学環境理工学部Acta Medica Okayama1341-90991212007合成変数の推定を利用した項目選択とその数値的検討2940ENYuichiMoriKaoruFuedaMasayaIizuka10.18926/fest/11429A 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.No potential conflict of interest relevant to this article was reported.Acta Medica Okayama2003Variable selection in multivariate methods and its softwareENMasayaIizukaNo potential conflict of interest relevant to this article was reported.