Application of WGAN-GP in recommendation and Questioning the relevance of GAN-based approaches. (arXiv:2204.12527v1 [cs.IR])

Many neural-based recommender systems were proposed in recent years and part
of them used Generative Adversarial Networks (GAN) to model user-item
interactions. However, the exploration of Wasserstein GAN with Gradient Penalty
(WGAN-GP) on recommendation has received relatively less scrutiny. In this
paper, we focus on two questions: 1- Can we successfully apply WGAN-GP on
recommendation and does this approach give an advantage compared to the best
GAN models? 2- Are GAN-based recommender systems relevant? To answer the first
question, we …

application arxiv gan recommendation wgan