Abstract
In this paper we present an automatic review generator system which can generate personalized reviews based on the user identity, product identity and designated rating the user wishes to allot to the review. We combine this with a sentiment analysis system which performs the complimentary task of assigning ratings to reviews based purely on the textual content of the review. We introduce an additional loss term to ensure cyclic consistency of the sentiment rating of the generated review with the conditioning rating used to generate the review. The introduction of this new loss term constraints the generation space while forcing it to generate reviews adhering better to the requested rating. The use of ‘soft’ generation and cyclic consistency allows us to train our model in an end to end fashion. We demonstrate the working of our model on product reviews from Amazon dataset.- Anthology ID:
- W18-6552
- Volume:
- Proceedings of the 11th International Conference on Natural Language Generation
- Month:
- November
- Year:
- 2018
- Address:
- Tilburg University, The Netherlands
- Editors:
- Emiel Krahmer, Albert Gatt, Martijn Goudbeek
- Venue:
- INLG
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 426–430
- Language:
- URL:
- https://aclanthology.org/W18-6552
- DOI:
- 10.18653/v1/W18-6552
- Cite (ACL):
- Vasu Sharma, Harsh Sharma, Ankita Bishnu, and Labhesh Patel. 2018. Cyclegen: Cyclic consistency based product review generator from attributes. In Proceedings of the 11th International Conference on Natural Language Generation, pages 426–430, Tilburg University, The Netherlands. Association for Computational Linguistics.
- Cite (Informal):
- Cyclegen: Cyclic consistency based product review generator from attributes (Sharma et al., INLG 2018)
- PDF:
- https://preview.aclanthology.org/ml4al-ingestion/W18-6552.pdf