@inproceedings{3753e52f784c4647bae9510fdfe6b0c3,
title = "Aspect-Based Sentiment Analysis and Singer Name Entity Recognition using Parameter Generation Network Based Transfer Learning",
abstract = "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.",
keywords = "Aspect-Based Sentiment Analysis, Gradient Adversarial Layer, Named Entity Recognition, Parameter Generation Network",
author = "Tseng, {Hsiao Wen} and Chang, {Chia Hui} and Chuang, {Hsiu Min}",
note = "Publisher Copyright: {\textcopyright} 2021 ROCLING 2021 - Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing. All rights reserved.; null ; Conference date: 15-10-2021 Through 16-10-2021",
year = "2021",
language = "???core.languages.en_GB???",
series = "ROCLING 2021 - Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing",
publisher = "The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)",
pages = "202--209",
editor = "Lung-Hao Lee and Chia-Hui Chang and Kuan-Yu Chen",
booktitle = "ROCLING 2021 - Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing",
}