128 citations · 192 across the 9 of their papers we have counts for
9 papers
Quality-Aware Collaborative Multi-Positive Contrastive Learning for Sequential Recommendation
Wei Wang, Yujie Lin, Moyan Zhang +5
The effectiveness of contrastive learning in sequential recommendation hinges on the construction of contrastive views, which ideally should be both semantically consistent and div…
Learnable Sequence Augmenter for Triplet Contrastive Learning in Sequential Recommendation
Wei Wang, Yujie Lin, Jianli Zhao +4
Most existing contrastive learning-based sequential recommendation (SR) methods rely on random operations (e.g., crop, reorder, and substitute) to generate augmented sequences. The…
Privacy-Preserving Sequential Recommendation with Collaborative Confusion
Wei Wang, Yujie Lin, Pengjie Ren +7
Sequential recommendation has attracted a lot of attention from both academia and industry, however the privacy risks associated to gathering and transferring users' personal inter…
A Self-Correcting Sequential Recommender
Yujie Lin, Chenyang Wang, Zhumin Chen +6
Sequential recommendations aim to capture users' preferences from their historical interactions so as to predict the next item that they will interact with. Sequential recommendati…
Modeling Sequential Recommendation as Missing Information Imputation
Yujie Lin, Zhumin Chen, Zhaochun Ren +5
Side information is being used extensively to improve the effectiveness of sequential recommendation models. It is said to help capture the transition patterns among items. Most pr…
Meta Matrix Factorization for Federated Rating Predictions
Yujie Lin, Pengjie Ren, Zhumin Chen +5
Federated recommender systems have distinct advantages in terms of privacy protection over traditional recommender systems that are centralized at a data center. However, previous…
Parallel Split-Join Networks for Shared-account Cross-domain Sequential Recommendations
Wenchao Sun, Muyang Ma, Pengjie Ren +5
Sequential recommendation is a task in which one models and uses sequential information about user behavior for recommendation purposes. We study sequential recommendation in a par…
Improving Outfit Recommendation with Co-supervision of Fashion Generation
Yujie Lin, Pengjie Ren, Zhumin Chen +3
The task of fashion recommendation includes two main challenges: visual understanding and visual matching. Visual understanding aims to extract effective visual features. Visual ma…
Explainable Outfit Recommendation with Joint Outfit Matching and Comment Generation
Yujie Lin, Pengjie Ren, Zhumin Chen +3
Most previous work on outfit recommendation focuses on designing visual features to enhance recommendations. Existing work neglects user comments of fashion items, which have been…