Collaborative Filtering Based on Diffusion Models: Unveiling the Potential of High-Order Connectivity

arXiv:2404.14240v1 Announce Type: cross
Abstract: A recent study has shown that diffusion models are well-suited for modeling the generative process of user-item interactions in recommender systems due to their denoising nature. However, existing diffusion model-based recommender systems do not explicitly leverage high-order connectivities that contain crucial collaborative signals for accurate recommendations. Addressing this gap, we propose CF-Diff, a new diffusion model-based collaborative filtering (CF) method, which is capable of making full use of collaborative signals along with multi-hop neighbors. Specifically, …

abstract arxiv collaborative collaborative filtering connectivity cs.ai cs.ir cs.it cs.lg cs.si denoising diffusion diffusion model diffusion models filtering generative however interactions math.it modeling nature process recommender systems study systems type