Cargando…
Personal Interest Attention Graph Neural Networks for Session-Based Recommendation
Session-based recommendations aim to predict a user’s next click based on the user’s current and historical sessions, which can be applied to shopping websites and APPs. Existing session-based recommendation methods cannot accurately capture the complex transitions between items. In addition, some a...
Autores principales: | Zhang, Xiangde, Zhou, Yuan, Wang, Jianping, Lu, Xiaojun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8618736/ https://www.ncbi.nlm.nih.gov/pubmed/34828197 http://dx.doi.org/10.3390/e23111500 |
Ejemplares similares
-
Session Recommendation Model Based on Context-Aware and Gated Graph Neural Networks
por: Li, Dan, et al.
Publicado: (2021) -
Self-supervised global context graph neural network for session-based recommendation
por: Chu, Fei, et al.
Publicado: (2022) -
Recipe Recommendation With Hierarchical Graph Attention Network
por: Tian, Yijun, et al.
Publicado: (2022) -
Graph neural networks for preference social recommendation
por: Ma, Gang-Feng, et al.
Publicado: (2023) -
A graph neural network framework based on preference-aware graph diffusion for recommendation
por: Shu, Tao, et al.
Publicado: (2022)