39 citations · 86 across the 4 of their papers we have counts for
8 papers · 1 filter
On the User Behavior Leakage from Recommender System Exposure
Xin Xin, Jiyuan Yang, Hanbing Wang +6
Modern recommender systems are trained to predict users potential future interactions from users historical behavior data. During the interaction process, despite the data coming f…
Improving Transformer-based Sequential Recommenders through Preference Editing
Muyang Ma, Pengjie Ren, Zhumin Chen +4
One of the key challenges in Sequential Recommendation (SR) is how to extract and represent user preferences. Traditional SR methods rely on the next item as the supervision signal…
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…
RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-based Recommendation
Pengjie Ren, Zhumin Chen, Jing Li +3
Recurrent neural networks for session-based recommendation have attracted a lot of attention recently because of their promising performance. repeat consumption is a common phenome…
Attentive Long Short-Term Preference Modeling for Personalized Product Search
Yangyang Guo, Zhiyong Cheng, Liqiang Nie +3
E-commerce users may expect different products even for the same query, due to their diverse personal preferences. It is well-known that there are two types of preferences: long-te…