339 citations · 1.4k across the 32 of their papers we have counts for
8 papers · 1 filter
CausalRec: Causal Inference for Visual Debiasing in Visually-Aware Recommendation
Ruihong Qiu, Sen Wang, Zhi Chen +2
Visually-aware recommendation on E-commerce platforms aims to leverage visual information of items to predict a user's preference. It is commonly observed that user's attention to…
Exploiting Cross-Session Information for Session-based Recommendation with Graph Neural Networks
Ruihong Qiu, Zi Huang, Jingjing Li +1
Different from the traditional recommender system, the session-based recommender system introduces the concept of the session, i.e., a sequence of interactions between a user and m…
GAG: Global Attributed Graph Neural Network for Streaming Session-based Recommendation
Ruihong Qiu, Hongzhi Yin, Zi Huang +1
Streaming session-based recommendation (SSR) is a challenging task that requires the recommender system to do the session-based recommendation (SR) in the streaming scenario. In th…
Try This Instead: Personalized and Interpretable Substitute Recommendation
Tong Chen, Hongzhi Yin, Guanhua Ye +3
As a fundamental yet significant process in personalized recommendation, candidate generation and suggestion effectively help users spot the most suitable items for them. Consequen…
Deep Collaborative Discrete Hashing with Semantic-Invariant Structure
Zijian Wang, Zheng Zhang, Yadan Luo +1
Existing deep hashing approaches fail to fully explore semantic correlations and neglect the effect of linguistic context on visual attention learning, leading to inferior performa…
Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks
Ruihong Qiu, Jingjing Li, Zi Huang +1
Predicting a user's preference in a short anonymous interaction session instead of long-term history is a challenging problem in the real-life session-based recommendation, e.g., e…
Exploring Auxiliary Context: Discrete Semantic Transfer Hashing for Scalable Image Retrieval
Lei Zhu, Zi Huang, Zhihui Li +2
Unsupervised hashing can desirably support scalable content-based image retrieval (SCBIR) for its appealing advantages of semantic label independence, memory and search efficiency.…
Collaborative Learning for Extremely Low Bit Asymmetric Hashing
Yadan Luo, Zi Huang, Yang Li +3
Hashing techniques are in great demand for a wide range of real-world applications such as image retrieval and network compression. Nevertheless, existing approaches could hardly g…