On the Use of User-generated Content in Critiquing Recommendation
David Contreras Aguilar, Salam oacute Maria · Frontiers in artificial intelligence and applications · 2015
User-generated content is any form of content that is created by users of an online system or service, often made by available via social media websites. Usually, on eCommerce websites, user-generated content is created by means of reviews, opinions or ratings about products. We consider that a wealth of collaborative information (i.e., user-generated content) about the products can now be used in an critiquing recommendation process to improve its outcome. In this paper we describe and analyze two approaches for adding user-generated content to a critiquing-based recommender. Our analysis includes two recommendation scenarios and the results indicate that efficiency is improved in both of them when user-generated content is added to the recommender.