| dc.contributor | 語言所 | |
| dc.creator (作者) | 張瑜芸 | |
| dc.creator (作者) | Chang, Yu-Yun | |
| dc.creator (作者) | Chiang, Yi Fan;Lee, Chi-Ling;Liao, Heng-Chia;Tsai, Yi-Ting | |
| dc.date (日期) | 2021-10 | |
| dc.date.accessioned | 17-Feb-2023 15:08:27 (UTC+8) | - |
| dc.date.available | 17-Feb-2023 15:08:27 (UTC+8) | - |
| dc.date.issued (上傳時間) | 17-Feb-2023 15:08:27 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/143480 | - |
| dc.description.abstract (摘要) | 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. | |
| dc.format.extent | 107 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | 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 | |
| dc.title (題名) | Improved text classification of long-term care materials | |
| dc.type (資料類型) | conference | |
