2017 EMNLP EMNLP 2017

Opinion Recommendation Using A Neural Model

Abstract

AbstractWe 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 Yelpโ€™s own ratings. our methods give better results compared to several pipelines baselines.

๐ŸŒ‰ Interdisciplinary Bridge โ€” Data Science & Analytics and Deep Learning and Natural Language Processing
๐Ÿงญ Keyword Pioneer โ€” review generation
๐Ÿฃ Hot Topic Early Bird โ€” opinion mining
๐Ÿ Cross-Pollinator โ€” Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio