Enhance Weakly-Supervised Aspect Detection with External Knowledge (Student Abstract)
Abstract
Aspect detection aims to identify aspects of reviews and is an essential up-stream task of opinion mining and so on. However, existing weakly-supervised methods suffer from lacking the ability of identifying implicit aspects with infrequent aspect terms and "Misc" aspects. To tackle these problems, we propose to enhance the representation of segment with external knowledge by a weakly-supervised method. Experiments demonstrate the effectiveness of our model and the improvement by incorporating external knowledge.
Cite
Text
Zheng et al. "Enhance Weakly-Supervised Aspect Detection with External Knowledge (Student Abstract)." AAAI Conference on Artificial Intelligence, 2022. doi:10.1609/AAAI.V36I11.21696Markdown
[Zheng et al. "Enhance Weakly-Supervised Aspect Detection with External Knowledge (Student Abstract)." AAAI Conference on Artificial Intelligence, 2022.](https://mlanthology.org/aaai/2022/zheng2022aaai-enhance/) doi:10.1609/AAAI.V36I11.21696BibTeX
@inproceedings{zheng2022aaai-enhance,
title = {{Enhance Weakly-Supervised Aspect Detection with External Knowledge (Student Abstract)}},
author = {Zheng, Zhuoming and Cai, Yi and Li, Liuwu},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2022},
pages = {13119-13120},
doi = {10.1609/AAAI.V36I11.21696},
url = {https://mlanthology.org/aaai/2022/zheng2022aaai-enhance/}
}