@inproceedings{wang-zhang-2017-opinion,
title = "Opinion Recommendation Using A Neural Model",
author = "Wang, Zhongqing and
Zhang, Yue",
editor = "Palmer, Martha and
Hwa, Rebecca and
Riedel, Sebastian",
booktitle = "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing",
month = sep,
year = "2017",
address = "Copenhagen, Denmark",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D17-1170",
doi = "10.18653/v1/D17-1170",
pages = "1626--1637",
abstract = "We present opinion recommendation, a novel task of jointly generating a review with a rating score that a certain user would give to a certain product which is unreviewed by the user, given existing reviews to the product by other users, and the reviews that the user has given to other products. A characteristic of opinion recommendation is the reliance of multiple data sources for multi-task joint learning. We use a single neural network to model users and products, generating customised product representations using a deep memory network, from which customised ratings and reviews are constructed jointly. Results show that our opinion recommendation system gives ratings that are closer to real user ratings on Yelp.com data compared with Yelp{'}s own ratings. our methods give better results compared to several pipelines baselines.",
}
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%0 Conference Proceedings
%T Opinion Recommendation Using A Neural Model
%A Wang, Zhongqing
%A Zhang, Yue
%Y Palmer, Martha
%Y Hwa, Rebecca
%Y Riedel, Sebastian
%S Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F wang-zhang-2017-opinion
%X We present opinion recommendation, a novel task of jointly generating a review with a rating score that a certain user would give to a certain product which is unreviewed by the user, given existing reviews to the product by other users, and the reviews that the user has given to other products. A characteristic of opinion recommendation is the reliance of multiple data sources for multi-task joint learning. We use a single neural network to model users and products, generating customised product representations using a deep memory network, from which customised ratings and reviews are constructed jointly. Results show that our opinion recommendation system gives ratings that are closer to real user ratings on Yelp.com data compared with Yelp’s own ratings. our methods give better results compared to several pipelines baselines.
%R 10.18653/v1/D17-1170
%U https://aclanthology.org/D17-1170
%U https://doi.org/10.18653/v1/D17-1170
%P 1626-1637
Markdown (Informal)
[Opinion Recommendation Using A Neural Model](https://aclanthology.org/D17-1170) (Wang & Zhang, EMNLP 2017)
ACL
- Zhongqing Wang and Yue Zhang. 2017. Opinion Recommendation Using A Neural Model. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 1626–1637, Copenhagen, Denmark. Association for Computational Linguistics.