DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System

Understand

In general, recommendation can be viewed as a matching problem, i.e., match proper items for proper users.

• However, due to the huge semantic gap between users and items, it's almost impossible to directly match users and items in their initial representation spaces.
• To solve this problem, many methods have been studied, which can be generally categorized into two types, i.e., representation learning-based CF methods and matching function learning-based CF methods.
• Representation learning-based CF methods try to map users and items into a common representation space.