2 citations · 2 across the 3 of their papers we have counts for
5 papers
Eliminating Propagation Delay: Attention-Based Spatial-Temporal Fusion Graph Convolution Network for Traffic Flow Prediction
Jinpeng Chen, Ziyu Yu, Tao Wang +5
Predicting traffic flow is crucial to optimizing transportation systems and improving urban mobility. Many graph convolution-based models have been proposed to extract spatial-temp…
STEP: Stepwise Curriculum Learning for Context-Knowledge Fusion in Conversational Recommendation
Zhenye Yang, Jinpeng Chen, Huan Li +6
Conversational recommender systems (CRSs) aim to proactively capture user preferences through natural language dialogue and recommend high-quality items. To achieve this, CRS gathe…
Hierarchical Intent-guided Optimization with Pluggable LLM-Driven Semantics for Session-based Recommendation
Jinpeng Chen, Jianxiang He, Huan Li +5
Session-based Recommendation (SBR) aims to predict the next item a user will likely engage with, using their interaction sequence within an anonymous session. Existing SBR models o…
Leveraging Multimodal Data and Side Users for Diffusion Cross-Domain Recommendation
Fan Zhang, Jinpeng Chen, Huan Li +6
Cross-domain recommendation (CDR) aims to address the persistent cold-start problem in Recommender Systems. Current CDR research concentrates on transferring cold-start users' info…
SR-HetGNN:Session-based Recommendation with Heterogeneous Graph Neural Network
Jinpeng Chen, Haiyang Li, Xudong Zhang +4
The Session-Based Recommendation System aims to predict the user's next click based on their previous session sequence. The current studies generally learn user preferences accordi…