From More-Like-This to Better-Than-This: Hotel Recommendations from User Generated Reviews

UMAP ’16, Halifax, NS, CanadaTo help users discover relevant products and items recommender systems must learn about the likes and dislikes of users and the pros and cons of items. In this paper, we present a novel approach to building rich feature-based user profiles and item descriptions by mining user-generated reviews. We show how this information can be integrated into recommender systems to deliver better recommendations and an improved user experience.Science Foundation Irelan