32 citations · 45 across the 7 of their papers we have counts for
7 papers
Towards Open-world Cross-Domain Sequential Recommendation: A Model-Agnostic Contrastive Denoising Approach
Wujiang Xu, Xuying Ning, Wenfang Lin +7
Cross-domain sequential recommendation (CDSR) aims to address the data sparsity problems that exist in traditional sequential recommendation (SR) systems. The existing approaches a…
Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptions
Wujiang Xu, Qitian Wu, Runzhong Wang +5
Cross-Domain Sequential Recommendation (CDSR) methods aim to tackle the data sparsity and cold-start problems present in Single-Domain Sequential Recommendation (SDSR). Existing CD…
Neural Node Matching for Multi-Target Cross Domain Recommendation
Wujiang Xu, Shaoshuai Li, Mingming Ha +5
Multi-Target Cross Domain Recommendation(CDR) has attracted a surge of interest recently, which intends to improve the recommendation performance in multiple domains (or systems) s…
Adaptive Pattern Extraction Multi-Task Learning for Multi-Step Conversion Estimations
Xuewen Tao, Mingming Ha, Xiaobo Guo +3
Multi-task learning (MTL) has been successfully used in many real-world applications, which aims to simultaneously solve multiple tasks with a single model. The general idea of mul…
Poincaré Heterogeneous Graph Neural Networks for Sequential Recommendation
Naicheng Guo, Xiaolei Liu, Shaoshuai Li +5
Sequential recommendation (SR) learns users' preferences by capturing the sequential patterns from users' behaviors evolution. As discussed in many works, user-item interactions of…
MHSCNet: A Multimodal Hierarchical Shot-aware Convolutional Network for Video Summarization
Wujiang Xu, Runzhong Wang, Xiaobo Guo +6
Video summarization intends to produce a concise video summary by effectively capturing and combining the most informative parts of the whole content. Existing approaches for video…
HCGR: Hyperbolic Contrastive Graph Representation Learning for Session-based Recommendation
Naicheng Guo, Xiaolei Liu, Shaoshuai Li +6
Session-based recommendation (SBR) learns users' preferences by capturing the short-term and sequential patterns from the evolution of user behaviors. Among the studies in the SBR…