Poincaré Heterogeneous Graph Neural Networks for Sequential Recommendation

Poincaré Heterogeneous Graph Neural Networks for Sequential Recommendation

Sequential recommendation (SR) learns users' preferences by capturing the sequential patterns from users' behaviors evolution. As discussed in many works, user-item interactions of SR generally present the intrinsic power-law distribution, which can be ascended to hierarchy-like structures...

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Bibliographic Details
Main Authors: Gao, K. (Author), Guo, N. (Author), Guo, S. (Author), Guo, X. (Author), Han, B. (Author), Li, S. (Author), Liu, X. (Author), Ma, Q. (Author), Zheng, L. (Author)
Format: Article
Language:English
Published: Association for Computing Machinery 2023
Subjects:
behaviors modeling
Behaviour models
Directed graphs
Euclidean spaces
Geometry
Graph neural networks
Heterogeneous graph
Hierarchical information
Hyperbolic learning
Learn+
Poincare
Sequential patterns
session-based recommendation
Session-based recommendation
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