4 papers
Causal-Invariant Cross-Domain Out-of-Distribution Recommendation
Jiajie Zhu, Yan Wang, Feng Zhu +3
Cross-Domain Recommendation (CDR) aims to leverage knowledge from a relatively data-richer source domain to address the data sparsity problem in a relatively data-sparser target do…
Next Point-of-interest (POI) Recommendation Model Based on Multi-modal Spatio-temporal Context Feature Embedding
Lingyu Zhang, Pengfei Xu, Rui Ban +4
Predicting the next pickup location of individual users is a fundamental problem in intelligent mobility systems, which requires modeling personalized travel behaviors under comple…
Diagnostic-Guided Dynamic Profile Optimization for LLM-based User Simulators in Sequential Recommendation
Hongyang Liu, Zhu Sun, Tianjun Wei +3
Recent advances in large language models (LLMs) have enabled realistic user simulators for developing and evaluating recommender systems (RSs). However, existing LLM-based simulato…
Causal Deconfounding via Confounder Disentanglement for Dual-Target Cross-Domain Recommendation
Jiajie Zhu, Yan Wang, Feng Zhu +1
In recent years, dual-target Cross-Domain Recommendation (CDR) has been proposed to capture comprehensive user preferences in order to ultimately enhance the recommendation accurac…