@InProceedings{wang-zhang:2017:EMNLP2017,
  author    = {Wang, Zhongqing  and  Zhang, Yue},
  title     = {Opinion Recommendation Using A Neural Model},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  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.},
  url       = {https://www.aclweb.org/anthology/D17-1170}
}