166 citations · 631 across the 64 of their papers we have counts for
7 papers · 1 filter
UnifiedSSR: A Unified Framework of Sequential Search and Recommendation
Jiayi Xie, Shang Liu, Gao Cong +1
In this work, we propose a Unified framework of Sequential Search and Recommendation (UnifiedSSR) for joint learning of user behavior history in both search and recommendation scen…
Mutually-Regularized Dual Collaborative Variational Auto-encoder for Recommendation Systems
Yaochen Zhu, Zhenzhong Chen
Recently, user-oriented auto-encoders (UAEs) have been widely used in recommender systems to learn semantic representations of users based on their historical ratings. However, sin…
Hierarchical Transformer with Spatio-Temporal Context Aggregation for Next Point-of-Interest Recommendation
Jiayi Xie, Zhenzhong Chen
Next point-of-interest (POI) recommendation is a critical task in location-based social networks, yet remains challenging due to a high degree of variation and personalization exhi…
Deep Deconfounded Content-based Tag Recommendation for UGC with Causal Intervention
Yaochen Zhu, Xubin Ren, Jing Yi +1
Traditional content-based tag recommender systems directly learn the association between user-generated content (UGC) and tags based on collected UGC-tag pairs. However, since a UG…
Multi-Auxiliary Augmented Collaborative Variational Auto-encoder for Tag Recommendation
Jing Yi, Xubin Ren, Zhenzhong Chen
Recommending appropriate tags to items can facilitate content organization, retrieval, consumption and other applications, where hybrid tag recommender systems have been utilized t…
Variational Bandwidth Auto-encoder for Hybrid Recommender Systems
Yaochen Zhu, Zhenzhong Chen
Hybrid recommendations have recently attracted a lot of attention where user features are utilized as auxiliary information to address the sparsity problem caused by insufficient u…
A Review-Driven Neural Model for Sequential Recommendation
Chenliang Li, Xichuan Niu, Xiangyang Luo +2
Writing review for a purchased item is a unique channel to express a user's opinion in E-Commerce. Recently, many deep learning based solutions have been proposed by exploiting use…