Low-frequency spectral graph convolution networks with one-hop connections information for personalized tag recommendation

Low-frequency spectral graph convolution networks with one-hop connections information for personalized tag recommendation

Abstract Graph neural networks (GNNs) have gained prominence as an effective technique for representation learning and have found wide application in tag recommendation tasks. Existing approaches aim to encode the hidden collaborative information among entities into embedding representations by prop...

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Bibliographic Details
Main Authors: Zhengshun Fei, Haotian Zhou, Jinglong Wang, Gui Chen, Xinjian Xiang
Format: Article
Language:English
Published: Springer 2024-11-01
Series:Complex & Intelligent Systems
Subjects:
Recommendation systems
Personalized tag recommendation
Graph convolutional network
Representation learning
Online Access:https://doi.org/10.1007/s40747-024-01643-5
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https://doi.org/10.1007/s40747-024-01643-5

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