2026-03-16T00:51:37Z https://ipsj.ixsq.nii.ac.jp/oai

oai:ipsj.ixsq.nii.ac.jp:00229840 2025-01-19T11:23:45Z 6504:11436:11440

The Significant Factors that Affect the Accuracy on Classifying English IBIS Datasets 董, 一涵 丁, 世堯 Jawad, HAQBEEN 伊藤, 孝行 人工知能と認知科学 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. 情報処理学会 2023-02-16 eng conference paper https://ipsj.ixsq.nii.ac.jp/records/229840 AN00349328 第85回全国大会講演論文集 2023 1 77 78 https://ipsj.ixsq.nii.ac.jp/record/229840/files/IPSJ-Z85-7C-01.pdf application/pdf 1.4 MB 2023-11-17