Scratch‐RL: A preference‐driven adversarial reinforcement reasoning framework over knowledge graphs for explainable recommendation of Scratch

Abstract

Nowadays, Scratch, as a widely-used educational programming platform, has gathered a huge number of programming users all over the world. Facing massive programming resources, how to make satisfactory programming recommendations has attracted increasing attention, especially on explainable recommendations. Existing Scratch recommendation systems overlook to