Review Polarity-wise Recommender

Understand

Utilizing review information to enhance recommendation, the de facto review-involved recommender systems, have received increasing interests over the past few years.

• Thereinto, one advanced branch is to extract salient aspects from textual reviews (i.e., the item attributes that users express) and combine them with the matrix factorization technique.
• However, existing approaches all ignore the fact that semantically different reviews often include opposite aspect information.
• In particular, positive reviews usually express aspects that users prefer, while negative ones describe aspects that users reject.