@inproceedings{kruengkrai-2019-learning,
title = "Learning to Flip the Sentiment of Reviews from Non-Parallel Corpora",
author = "Kruengkrai, Canasai",
editor = "Inui, Kentaro and
Jiang, Jing and
Ng, Vincent and
Wan, Xiaojun",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-1659",
doi = "10.18653/v1/D19-1659",
pages = "6311--6316",
abstract = "Flipping sentiment while preserving sentence meaning is challenging because parallel sentences with the same content but different sentiment polarities are not always available for model learning. We introduce a method for acquiring imperfectly aligned sentences from non-parallel corpora and propose a model that learns to minimize the sentiment and content losses in a fully end-to-end manner. Our model is simple and offers well-balanced results across two domains: Yelp restaurant and Amazon product reviews.",
}
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%0 Conference Proceedings
%T Learning to Flip the Sentiment of Reviews from Non-Parallel Corpora
%A Kruengkrai, Canasai
%Y Inui, Kentaro
%Y Jiang, Jing
%Y Ng, Vincent
%Y Wan, Xiaojun
%S Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F kruengkrai-2019-learning
%X Flipping sentiment while preserving sentence meaning is challenging because parallel sentences with the same content but different sentiment polarities are not always available for model learning. We introduce a method for acquiring imperfectly aligned sentences from non-parallel corpora and propose a model that learns to minimize the sentiment and content losses in a fully end-to-end manner. Our model is simple and offers well-balanced results across two domains: Yelp restaurant and Amazon product reviews.
%R 10.18653/v1/D19-1659
%U https://aclanthology.org/D19-1659
%U https://doi.org/10.18653/v1/D19-1659
%P 6311-6316
Markdown (Informal)
[Learning to Flip the Sentiment of Reviews from Non-Parallel Corpora](https://aclanthology.org/D19-1659) (Kruengkrai, EMNLP-IJCNLP 2019)
ACL
- Canasai Kruengkrai. 2019. Learning to Flip the Sentiment of Reviews from Non-Parallel Corpora. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 6311–6316, Hong Kong, China. Association for Computational Linguistics.