no code implementations • ROCLING 2021 • Ching-Wen Hsu, Chun-Lin Chou, Hsuan Liu, Jheng-Long Wu
To evaluate the performance of different classifiers, we experiment with deep learning-based, machine learning-based, and BERT-based classifiers to automatically detect three sentiment indicators of an audience’s comments.
no code implementations • ROCLING 2021 • Hsuan-Tzu Shih, Yu-Cheng Chiu, Hsiao-Shih Chen, Jheng-Long Wu
In addition to assisting legislators in formulating laws, it can also provide other people with an understanding of the actual operation of the confiscation system.
no code implementations • ROCLING 2021 • Hsiao-Shih Chen, Pin-Chiung Chen, Shao-Cheng Huang, Yu-Cheng Chiu, Jheng-Long Wu
Sentiment analysis has become a popular research issue in recent years, especially on educational texts which is an important problem.
no code implementations • ROCLING 2022 • Fang-Ju Lee, Ying-Chun Lo, Jheng-Long Wu
Extracting relevant user behaviors through customer’s transaction description is one of the ways to collect customer information.
no code implementations • ROCLING 2022 • Sheng-Wei Huang, Wei-Yi Chung, Yu-Hsuan Wu, Chen-Chia Yu, Jheng-Long Wu
This paper creates the extended NTU irony corpus, which includes valence, arousal and irony intensities on sentence-level; and valence and arousal intensities on context-level, called Chinese Dimensional Valence-Arousal-Irony (CDVAI) dataset.
no code implementations • ROCLING 2022 • Sung-Ting Chiou, Sheng-Wei Huang, Ying-Chun Lo, Yu-Hsuan Wu, Jheng-Long Wu
Named entity recognition generally refers to entities with specific meanings in unstructured text, including names of people, places, organizations, dates, times, quantities, proper nouns and other words.