Learning to utilize auxiliary reviews for recommendation

Review-based recommender systems represent users and items with reviews associated with them. As such, the recommender systems are highly dependent on the number of reviews, which is usually few in number. Thus, they produce inaccurate recommendations to users who rarely wrote reviews. An approach to generate better recommendations for the cold-start users is to augment the scarce reviews using other reviews, which are called auxiliary reviews....