Maozu Guo

Partial Multi-label Learning with Label and Feature Collaboration

2020 · arXiv (Cornell University)

Partial multi-label learning (PML) models the scenario where each training instance is annotated with a set of candidate labels, and only some of the labels are relevant. The PML problem is practical in real-world scenarios, …

A Recommendation Approach Based on Heterogeneous Network and Dynamic Knowledge Graph

2024 · International Journal of Intelligent Systems

Besides data sparsity and cold start, recommender systems often face the problems of selection bias and exposure bias. These problems influence the accuracy of recommendations and easily lead to overrecommendations. This paper proposes a recommendation …