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政大機構典藏 > 外國語文學院 > 語言學研究所 > 會議論文 > Item 140.119/143480

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/143480

Title:	Improved text classification of long-term care materials
Authors:	張瑜芸 Chang, Yu-Yun Chiang, Yi Fan;Lee, Chi-Ling;Liao, Heng-Chia;Tsai, Yi-Ting
Contributors:	語言所
Date:	2021-10
Issue Date:	2023-02-17 15:08:27 (UTC+8)
Abstract:	Aging populations have posed a challenge to many countries including Taiwan, and with them come the issue of long-term care. Given the current context, the aim of this study was to explore the hotly-discussed subtopics in the field of long-term care, and identify its features through NLP. This study applied TF-IDF, the Logistic Regression model, and the Naive Bayes classifier to process data. In sum, the results showed that it reached a best F1-score of 0.920 in identification, and a best accuracy of 0.708 in classification. The results of this study could be used as a reference for future long-term care related applications.
Relation:	Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing (ROCLING 2021), Association for Computational Linguistics and Chinese Language Processing (ACLCLP), pp.294-300
Data Type:	conference
Appears in Collections:	[語言學研究所] 會議論文

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