… inference model of our graphless SimRec generates more … of GNN-based CF, our graph-less
SimRec model still signifcantly … In comparison, our graph-less SimRec model abandons …

… From the technical perspective, Collaborative Filtering (CF) is seen as an important factor in
… a novel Embedding-Less Graph Collaborative Filtering (EGCF) for recommendation, which …

… Additionally, we compare these graph models with traditional collaborative filtering models
that historically performed well in offline evaluations. Furthermore, we extend our study to two …

… Decorrelation Graph Collaborative Filtering (AFDGCF) … four representative graph collaborative
filtering models across four … landscape of graph collaborative filtering models. The code …

… In this section, we demonstrate the reason behind why message passing helps collaborative
filtering from two major perspectives: Firstly, we focus on inductive biases brought by the …

… method HiGSP for collaborative filtering. User segmentation … Then, we design a cluster-wise
filter module to recognize the … In addition, we design a globally-aware filter module, which …

… To encode the interaction patterns between users and items, we follow the common
collaborative filtering paradigm by embedding them into a 𝑑-dimensional latent space. Specifically, …

… Networks (DNN) in Collaborative Filtering (CF) recommendation … principles of both collaborative
filtering and deep neural … enhancing collaborative filtering systems with deep learning. …

… Collaborative Filtering The principle of collaborative filtering is that people tend to cluster …
Initially, collaborative filtering directly obtains user similarity through a co-occurrence matrix. …

… In this paper, we present MGCF, a collaborative filtering model guided by modality features,
specifically designed for the task of multi-modal recommendation. By harnessing both …