@article{oai:ipsj.ixsq.nii.ac.jp:00219097,
 author = {納谷, 大智 and 吉見, 毅彦 and Daichi, Naya and Takehiko, Yoshimi},
 issue = {8},
 journal = {情報処理学会論文誌},
 month = {Aug},
 note = {本研究では，日本語の文を対象とした感情推定において，従来とは異なる類似度測定尺度を利用することで推定精度を改善する．従来手法で用いられている類似度測定尺度は，日本語の文を対象としたとき，単語の出現順序（語順）に対する制約が緩すぎるか，あるいは厳しすぎる．このため，提案手法では，英語に比べて語順の自由度が高い日本語に適した類似度測定尺度として，日本語の文における語順の制約を考慮した機械翻訳の自動評価尺度を利用する．検証実験の結果，従来手法よりも提案手法の方が感情推定の正解率が高いことが確認された．, This study was aimed at improving the accuracy of emotion classification for Japanese sentences by using a novel similarity measure. Similarity measures used in existing methods are too strict or too lax in their consideration of the order of words during the processing of Japanese sentences. They fail to incorporate the fact that Japanese exhibits a higher degree of freedom in word order compared to English. To address this issue, our proposed method utilizes a similarity measure more suitable for Japanese. Our experimental results indicate that the proposed method exhibits higher classification accuracy than existing alternatives.},
 pages = {1383--1387},
 title = {大局的な語順を考慮した相関に基づく類似度測定による感情推定},
 volume = {63},
 year = {2022}
}