5 papers
Dual-Interest Sequential Product Recommendation With Multi-Granular SSM
Shuiying Liao, P. Y. Mok
Sequential recommendation aims to predict the next item a user will interact with based on their historical behavior. Advances in Transformers have significantly improved sequentia…
Adaptive Preference Modeling via Explicit Indirect Relational Learning for Personalized Fashion Matching
Shuiying Liao, Li Li, P. Y. Mok
Personalized fashion complementary recommendation requires jointly modeling user preferences and item compatibility under sparse and multimodal data conditions. Existing approaches…
PCGNet: Unifying Shared and Specific Information for Fashion Matching Recommendations
Shuiying Liao, P. Y. Mok
In fashion domain, recommending complementary clothing items that match selected pieces is a crucial cross-selling technique that improves customer satisfaction. Nevertheless, fash…
Hamiltonian Spectral-Temporal Dissipative Dynamics for Sequential Recommendation
Shuiying Liao, P. Y. Mok
Sequential recommendation requires understanding how user preferences evolve over time, yet most existing models treat such evolution as a first order process where the next state…
Consistency Regularization for Complementary Clothing Recommendations
Shuiying Liao, P. Y. Mok, Li Li
This paper reports on the development of a Consistency Regularized model for Bayesian Personalized Ranking (CR-BPR), addressing to the drawbacks in existing complementary clothing…