Int-GNN: A User Intention Aware Graph Neural Network for Session-Based Recommendation
Author:
Affiliation:
1. Harbin Institute of Technology,Computer Science & Technology,Shenzhen,China
2. JD Intelligent Cities Research, JD iCity,Beijing,China
3. Shenzhen Technology University,College of Big Data and Internet,Shenzhen,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10094559/10094560/10097031.pdf?arnumber=10097031
Reference22 articles.
1. Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation
2. Global Context Enhanced Graph Neural Networks for Session-based Recommendation
3. MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity Interactions
4. Sequential Modeling of Hierarchical User Intention and Preference for Next-item Recommendation
5. Adam: A method for stochastic optimization;kingma;ICLRE,2015
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1. How to Bridge Graph and Sequence Patterns in Session-Based Recommendation? A Self-Supervised Method;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14
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