Session-Based Recommendation with Graph Neural Networks
The problem of session-based recommendation aims to predict user actions based on anonymous sessions. Previous methods model a session as a sequence and estimate user representa...
Publications
3 shownSelf-supervised Graph Learning for Recommendation
Representation learning on user-item graph for recommendation has evolved\nfrom using single ID or interaction history to exploiting higher-order\nneighbors. This leads to the s...
RippleNet
To address the sparsity and cold start problem of collaborative filtering,\nresearchers usually make use of side information, such as social networks or\nitem attributes, to imp...
Frequent Co-Authors
Researcher Info
- h-index
- 3
- Publications
- 3
- Citations
- 3,567
- Institution
- Microsoft Research Asia (China)
External Links
Identifiers
- ORCID
- 0000-0001-5898-432X
Impact Metrics
h-index
3
h-index: Number of publications with at least h citations each.