The Significant Factors that Affect the Accuracy on Classifying English IBIS Datasets

• Item type: National Convention(1)
• 公開日: 2023-02-16
• タイトル: The Significant Factors that Affect the Accuracy on Classifying English IBIS Datasets
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 人工知能と認知科学
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_5794
• 資源タイプ: conference paper
• 著者所属: 京大
• 著者所属: 京大
• 著者所属: 京大
• 著者所属: 京大
• 著者名: 董, 一涵; 丁, 世堯; Jawad, HAQBEEN; 伊藤, 孝行
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: To apply machine-learning technology in facilitating the discussion, helping people reach a consensus and other fields, classifying discussion contents according to the labels of the issue-based information system is critical and inevitable. However, the accuracy of classifying and predicting the discussion contents written in English is not satisfying right now. In this paper, two different pre-trained language models are fine-tuned to classify and predict IBIS labels of English sentences that were picked from two real discussion records. Based on the baseline of accuracy, several improvement methods are raised and taken. By comparing those results, the significant factors affecting the accuracy will be found to raise more detailed methods to improve the results in further research.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00349328
• 書誌情報: 第85回全国大会講演論文集; 巻 2023, 号 1, p. 77-78, 発行日 2023-02-16
• 出版者 / 言語: ja
• 出版者: 情報処理学会