Search Results for author:
Found 4 papers, 3 papers with code
Star Graph Neural Networks for Session-based Recommendation
The proposed SGNN-HN applies a star graph neural network (SGNN) to model the complex transition relationship between items in an ongoing session.
Ranked #1 on
Session-Based Recommendations
on yoochoose1/64
Attribute-aware Diversification for Sequential Recommendations
Users prefer diverse recommendations over homogeneous ones.
Improving End-to-End Sequential Recommendations with Intent-aware Diversification
Then, we design an Intent-aware Diversity Promoting (IDP) loss to supervise the learning of the IIM module and force the model to take recommendation diversity into consideration during training.
Joint Neural Collaborative Filtering for Recommender Systems
Deep feature learning extracts feature representations of users and items with a deep learning architecture based on a user-item rating matrix.
