Generating Recommendation Dialogs by Extracting Information from User Reviews
Kevin Scott Reschke, Adam P. Vogel, Dan Jurafsky · 2013
Recommendation dialog systems help users navigate e-commerce listings by asking questions about users ’ preferences toward relevant domain attributes. We present a framework for generating and ranking fine-grained, highly relevant questions from user-generated reviews. We demonstrate our approach on a new dataset just released by Yelp, and release a new sentiment lexicon with 1329 adjectives for the restaurant domain. 1