Min Zhou

HICF: Hyperbolic Informative Collaborative Filtering

2022 · Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Considering the prevalence of the power-law distribution in user-item networks, hyperbolic space has attracted considerable attention and achieved impressive performance in the recommender system recently. The advantage of hyperbolic recommendation lies in that its exponentially …

Mitigating Semantic Confusion from Hostile Neighborhood for Graph Active Learning

2023

Graph Active Learning (GAL), which aims to find the most informative nodes in graphs for annotation to maximize the Graph Neural Networks (GNNs) performance, has attracted many research efforts but remains non-trivial challenges. One major …

HRCF: Enhancing Collaborative Filtering via Hyperbolic Geometric Regularization

2022 · Proceedings of the ACM Web Conference 2022

In large-scale recommender systems, the user-item networks are generally scale-free or expand exponentially. For the representation of the user and item, the latent features (a.k.a, embeddings) depend on how well the embedding space matches the …