5 citations · 11 across the 4 of their papers we have counts for
4 papers
Knowledge Graph-based Session Recommendation with Adaptive Propagation
Yu Wang, Amin Javari, Janani Balaji +3
Session-based recommender systems (SBRSs) predict users' next interacted items based on their historical activities. While most SBRSs capture purchasing intentions locally within e…
Hierarchical Multi-Task Learning Framework for Session-based Recommendations
Sejoon Oh, Walid Shalaby, Amir Afsharinejad +1
While session-based recommender systems (SBRSs) have shown superior recommendation performance, multi-task learning (MTL) has been adopted by SBRSs to enhance their prediction accu…
Local Boosting for Weakly-Supervised Learning
Rongzhi Zhang, Yue Yu, Jiaming Shen +2
Boosting is a commonly used technique to enhance the performance of a set of base models by combining them into a strong ensemble model. Though widely adopted, boosting is typicall…
Adaptive Multi-view Rule Discovery for Weakly-Supervised Compatible Products Prediction
Rongzhi Zhang, Rebecca West, Xiquan Cui +1
On e-commerce platforms, predicting if two products are compatible with each other is an important functionality to achieve trustworthy product recommendation and search experience…