Zhenlei Wang

Unbiased Sequential Recommendation with Latent Confounders

2022 · Proceedings of the ACM Web Conference 2022

Sequential recommendation holds the promise of understanding user preference by capturing successive behavior correlations. Existing research focus on designing different models for better fitting the offline datasets. However, the observational data may have been contaminated …

Sequential Recommendation with Decomposed Item Feature Routing

2022 · Proceedings of the ACM Web Conference 2022

Sequential recommendation basically aims to capture user evolving preference. Intuitively, a user interacts with an item usually because of some specific feature, and user evolving preference is essentially determined by a series of important features …

Counterfactual Data-Augmented Sequential Recommendation

2021

Sequential recommendation aims at predicting users' preferences based on their historical behaviors. However, this recommendation strategy may not perform well in practice due to the sparsity of the real-world data. In this paper, we propose …