Yuan Lin
ABSTRACT
Recommendation systems can help users process large amounts of information, and generative adversarial networks (GANs) show great potential in recommendation systems. In this paper, we propose a new GAN model to enhance the information flow within the generator based on the information flow between the original generator and discriminator. Our experimental results indicate that our model reduces the discrepancy between the generator and the discriminator. Both the generator and discriminator yield considerable performance improvements compared to other strong baselines. The improvements by NDCG@3 and MRR are significant, which can reach 30.98% and 30.17%, respectively.
Supplemental Material
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Index Terms
- Info-flow Enhanced GANs for Recommender
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