Aspect-Based Sentiment Analysis and Singer Name Entity Recognition using Parameter Generation Network Based Transfer Learning

Hsiao Wen Tseng, Chia Hui Chang, Hsiu Min Chuang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

When we are interested in a certain domain, we can collect and analyze data from the Internet. The newly collected data is not labeled, so the use of labeled data is hoped to be helpful to the new data. We perform name entity recognition (NER) and aspect-based sentiment analysis (ABSA) in multi-task learning, and combine parameter generation network (Jia et al., 2019) and DANN architecture (Ganin and Lempitsky, 2015) to build the model. In the NER task, the data is labeled with Tie, Break, and the task weight is adjusted according to the loss change rate of each task using Dynamic Weight Average (DWA) (Liu et al., 2019). This study used two different source domain data sets. The experimental results show that Tie, Break can improve the results of the model: DWA can have better performance in the results; the combination of parameter generation network and gradient reversal layer can be used for every good learning in different domain.

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主出版物標題ROCLING 2021 - Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing
編輯Lung-Hao Lee, Chia-Hui Chang, Kuan-Yu Chen
發行者The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
頁面202-209
頁數8
ISBN(電子)9789869576949
出版狀態已出版 - 2021
事件33rd Conference on Computational Linguistics and Speech Processing, ROCLING 2021 - Taoyuan, Taiwan
持續時間: 15 10月 202116 10月 2021

出版系列

名字ROCLING 2021 - Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing

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???event.eventtypes.event.conference???33rd Conference on Computational Linguistics and Speech Processing, ROCLING 2021
國家/地區Taiwan
城市Taoyuan
期間15/10/2116/10/21

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